Publications

I no longer maintain this page. With few exceptions, my papers are first posted on arxiv.org. You can also find my publications on Google Scholar

 

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  2025 (1)
SPARC: Score Prompting and Adaptive Fusion for Zero-Shot Multi-Label Recognition in Vision-Language Models. Miller, K.; Mishra, S.; Gangrade, A.; Saenko, K.; and Saligrama, V. CoRR, abs/2502.16911. 2025.
SPARC: Score Prompting and Adaptive Fusion for Zero-Shot Multi-Label Recognition in Vision-Language Models [link]Paper   doi   link   bibtex  
  2024 (6)
Interpretable Compositional Representations for Robust Few-Shot Generalization. Mishra, S.; Zhu, P.; and Saligrama, V. IEEE Trans. Pattern Anal. Mach. Intell., 46(3): 1496–1512. 2024.
Interpretable Compositional Representations for Robust Few-Shot Generalization [link]Paper   doi   link   bibtex   1 download  
Safe Linear Bandits over Unknown Polytopes. Gangrade, A.; Chen, T.; and Saligrama, V. In The Thirty Seventh Annual Conference on Learning Theory, June 30 - July 3, 2023, Edmonton, Canada, pages 1755–1795, 2024.
Safe Linear Bandits over Unknown Polytopes [link]Paper   link   bibtex   1 download  
Testing the Feasibility of Linear Programs with Bandit Feedback. Gangrade, A.; Gopalan, A.; Saligrama, V.; and Scott, C. In Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024, 2024.
Testing the Feasibility of Linear Programs with Bandit Feedback [link]Paper   link   bibtex  
SynCDR : Training Cross Domain Retrieval Models with Synthetic Data. Mishra, S.; Saenko, K.; and Saligrama, V. CoRR, abs/2401.00420. 2024.
SynCDR : Training Cross Domain Retrieval Models with Synthetic Data [link]Paper   doi   link   bibtex   1 download  
Testing the Feasibility of Linear Programs with Bandit Feedback. Gangrade, A.; Gopalan, A.; Saligrama, V.; and Scott, C. CoRR, abs/2406.15648. 2024.
Testing the Feasibility of Linear Programs with Bandit Feedback [link]Paper   doi   link   bibtex  
Deep Companion Learning: Enhancing Generalization Through Historical Consistency. Zhu, R.; and Saligrama, V. CoRR, abs/2407.18821. 2024.
Deep Companion Learning: Enhancing Generalization Through Historical Consistency [link]Paper   doi   link   bibtex  
  2023 (10)
Ideology Prediction from Scarce and Biased Supervision: Learn to Disregard the "What" and Focus on the "How"!. Chen, C.; Walker, D.; and Saligrama, V. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2023, Toronto, Canada, July 9-14, 2023, pages 9529–9549, 2023.
Ideology Prediction from Scarce and Biased Supervision: Learn to Disregard the "What" and Focus on the "How"! [link]Paper   doi   link   bibtex  
Fine-grained Few-shot Recognition by Deep Object Parsing. Zhu, R.; Zhu, P.; Mishra, S.; and Saligrama, V. In 34th British Machine Vision Conference 2023, BMVC 2023, Aberdeen, UK, November 20-24, 2023, pages 330–331, 2023.
Fine-grained Few-shot Recognition by Deep Object Parsing [link]Paper   link   bibtex  
Learning to Drive Anywhere. Zhu, R.; Huang, P.; Ohn-Bar, E.; and Saligrama, V. In Conference on Robot Learning, CoRL 2023, 6-9 November 2023, Atlanta, GA, USA, pages 3631–3653, 2023.
Learning to Drive Anywhere [link]Paper   link   bibtex  
Scaffolding a Student to Instill Knowledge. Kag, A.; Acar, D. A. E.; Gangrade, A.; and Saligrama, V. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, 2023.
Scaffolding a Student to Instill Knowledge [link]Paper   link   bibtex   1 download  
Efficient Edge Inference by Selective Query. Kag, A.; Fedorov, I.; Gangrade, A.; Whatmough, P. N.; and Saligrama, V. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023, 2023.
Efficient Edge Inference by Selective Query [link]Paper   link   bibtex   2 downloads  
InfoCD: A Contrastive Chamfer Distance Loss for Point Cloud Completion. Lin, F.; Yue, Y.; Zhang, Z.; Hou, S.; Yamada, K. D.; Kolachalama, V.; and Saligrama, V. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023.
InfoCD: A Contrastive Chamfer Distance Loss for Point Cloud Completion [link]Paper   link   bibtex  
Learning Human Action Recognition Representations Without Real Humans. Zhong, H.; Mishra, S.; Kim, D.; Jin, S.; Panda, R.; Kuehne, H.; Karlinsky, L.; Saligrama, V.; Oliva, A.; and Feris, R. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023.
Learning Human Action Recognition Representations Without Real Humans [link]Paper   link   bibtex  
Filtering Context Mitigates Scarcity and Selection Bias in Political Ideology Prediction. Chen, C.; Walker, D.; and Saligrama, V. CoRR, abs/2302.00239. 2023.
Filtering Context Mitigates Scarcity and Selection Bias in Political Ideology Prediction [link]Paper   doi   link   bibtex   1 download  
Learning to Drive Anywhere. Zhu, R.; Huang, P.; Ohn-Bar, E.; and Saligrama, V. CoRR, abs/2309.12295. 2023.
Learning to Drive Anywhere [link]Paper   doi   link   bibtex  
Learning Human Action Recognition Representations Without Real Humans. Zhong, H.; Mishra, S.; Kim, D.; Jin, S.; Panda, R.; Kuehne, H.; Karlinsky, L.; Saligrama, V.; Oliva, A.; and Feris, R. CoRR, abs/2311.06231. 2023.
Learning Human Action Recognition Representations Without Real Humans [link]Paper   doi   link   bibtex  
  2022 (11)
Condensing CNNs with Partial Differential Equations. Kag, A.; and Saligrama, V. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022, pages 600–609, 2022.
Condensing CNNs with Partial Differential Equations [link]Paper   doi   link   bibtex   1 download  
Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data. Mishra, S.; Panda, R.; Phoo, C. P.; Chen, C. R.; Karlinsky, L.; Saenko, K.; Saligrama, V.; and Feris, R. S. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022, pages 9184–9194, 2022.
Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data [link]Paper   doi   link   bibtex   1 download  
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk. Chen, T.; Gangrade, A.; and Saligrama, V. In International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, pages 3123–3148, 2022.
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk [link]Paper   link   bibtex   4 downloads  
ActiveHedge: Hedge meets Active Learning. Kumar, B.; Abernethy, J. D.; and Saligrama, V. In International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, pages 11694–11709, 2022.
ActiveHedge: Hedge meets Active Learning [link]Paper   link   bibtex  
Faster Algorithms for Learning Convex Functions. Siahkamari, A.; Acar, D. A. E.; Liao, C.; Geyer, K. L.; Saligrama, V.; and Kulis, B. In International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, pages 20176–20194, 2022.
Faster Algorithms for Learning Convex Functions [link]Paper   link   bibtex  
How Transferable are Video Representations Based on Synthetic Data?. Kim, Y.; Mishra, S.; Jin, S.; Panda, R.; Kuehne, H.; Karlinsky, L.; Saligrama, V.; Saenko, K.; Oliva, A.; and Feris, R. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022, 2022.
How Transferable are Video Representations Based on Synthetic Data? [link]Paper   link   bibtex  
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk. Chen, T.; Gangrade, A.; and Saligrama, V. CoRR, abs/2204.00706. 2022.
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk [link]Paper   doi   link   bibtex   4 downloads  
Learning Compositional Representations for Effective Low-Shot Generalization. Mishra, S.; Zhu, P.; and Saligrama, V. CoRR, abs/2204.08090. 2022.
Learning Compositional Representations for Effective Low-Shot Generalization [link]Paper   doi   link   bibtex  
FedHeN: Federated Learning in Heterogeneous Networks. Acar, D. A. E.; and Saligrama, V. CoRR, abs/2207.03031. 2022.
FedHeN: Federated Learning in Heterogeneous Networks [link]Paper   doi   link   bibtex  
Fine-grained Few-shot Recognition by Deep Object Parsing. Zhu, P.; Zhu, R.; Mishra, S.; and Saligrama, V. CoRR, abs/2207.07110. 2022.
Fine-grained Few-shot Recognition by Deep Object Parsing [link]Paper   doi   link   bibtex  
A Doubly Optimistic Strategy for Safe Linear Bandits. Chen, T.; Gangrade, A.; and Saligrama, V. CoRR, abs/2209.13694. 2022.
A Doubly Optimistic Strategy for Safe Linear Bandits [link]Paper   doi   link   bibtex   1 download  
  2021 (18)
Selective Classification via One-Sided Prediction. Gangrade, A.; Kag, A.; and Saligrama, V. In The 24th International Conference on Artificial Intelligence and Statistics, AISTATS 2021, April 13-15, 2021, Virtual Event, pages 2179–2187, 2021.
Selective Classification via One-Sided Prediction [link]Paper   link   bibtex   1 download  
Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency. Mishra, S.; Saenko, K.; and Saligrama, V. In 32nd British Machine Vision Conference 2021, BMVC 2021, Online, November 22-25, 2021, pages 177, 2021.
Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency [pdf]Paper   link   bibtex  
Effectively Leveraging Attributes for Visual Similarity. Mishra, S.; Zhang, Z.; Shen, Y.; Kumar, R.; Saligrama, V.; and Plummer, B. A. In IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2021, virtual, June 19-25, 2021, pages 3904–3909, 2021.
Effectively Leveraging Attributes for Visual Similarity [link]Paper   doi   link   bibtex   1 download  
Time Adaptive Recurrent Neural Network. Kag, A.; and Saligrama, V. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19-25, 2021, pages 15149–15158, 2021.
Time Adaptive Recurrent Neural Network [link]Paper   doi   link   bibtex   1 download  
Effectively Leveraging Attributes for Visual Similarity. Mishra, S.; Zhang, Z.; Shen, Y.; Kumar, R.; Saligrama, V.; and Plummer, B. A. In 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021, Montreal, QC, Canada, October 10-17, 2021, pages 995–1004, 2021.
Effectively Leveraging Attributes for Visual Similarity [link]Paper   doi   link   bibtex   1 download  
Federated Learning Based on Dynamic Regularization. Acar, D. A. E.; Zhao, Y.; Navarro, R. M.; Mattina, M.; Whatmough, P. N.; and Saligrama, V. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021, 2021.
Federated Learning Based on Dynamic Regularization [link]Paper   link   bibtex  
Debiasing Model Updates for Improving Personalized Federated Training. Acar, D. A. E.; Zhao, Y.; Zhu, R.; Navarro, R. M.; Mattina, M.; Whatmough, P. N.; and Saligrama, V. In Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, pages 21–31, 2021.
Debiasing Model Updates for Improving Personalized Federated Training [link]Paper   link   bibtex  
Memory Efficient Online Meta Learning. Acar, D. A. E.; Zhu, R.; and Saligrama, V. In Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, pages 32–42, 2021.
Memory Efficient Online Meta Learning [link]Paper   link   bibtex  
Training Recurrent Neural Networks via Forward Propagation Through Time. Kag, A.; and Saligrama, V. In Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event, pages 5189–5200, 2021.
Training Recurrent Neural Networks via Forward Propagation Through Time [link]Paper   link   bibtex  
Online Selective Classification with Limited Feedback. Gangrade, A.; Kag, A.; Cutkosky, A.; and Saligrama, V. In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, pages 14529–14541, 2021.
Online Selective Classification with Limited Feedback [link]Paper   link   bibtex  
Bandit Quickest Changepoint Detection. Gopalan, A.; Lakshminarayanan, B.; and Saligrama, V. In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, pages 29064–29073, 2021.
Bandit Quickest Changepoint Detection [link]Paper   link   bibtex  
Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency. Mishra, S.; Saenko, K.; and Saligrama, V. CoRR, abs/2101.12727. 2021.
Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency [link]Paper   link   bibtex  
Effectively Leveraging Attributes for Visual Similarity. Mishra, S.; Zhang, Z.; Shen, Y.; Kumar, R.; Saligrama, V.; and Plummer, B. A. CoRR, abs/2105.01695. 2021.
Effectively Leveraging Attributes for Visual Similarity [link]Paper   link   bibtex   1 download  
Bandit Quickest Changepoint Detection. Gopalan, A.; Saligrama, V.; and Lakshminarayanan, B. CoRR, abs/2107.10492. 2021.
Bandit Quickest Changepoint Detection [link]Paper   link   bibtex  
Online Selective Classification with Limited Feedback. Gangrade, A.; Kag, A.; Cutkosky, A.; and Saligrama, V. CoRR, abs/2110.14243. 2021.
Online Selective Classification with Limited Feedback [link]Paper   link   bibtex  
Faster Convex Lipschitz Regression via 2-block ADMM. Siahkamari, A.; Acar, D. A. E.; Liao, C.; Geyer, K.; Saligrama, V.; and Kulis, B. CoRR, abs/2111.01348. 2021.
Faster Convex Lipschitz Regression via 2-block ADMM [link]Paper   link   bibtex  
Federated Learning Based on Dynamic Regularization. Acar, D. A. E.; Zhao, Y.; Navarro, R. M.; Mattina, M.; Whatmough, P. N.; and Saligrama, V. CoRR, abs/2111.04263. 2021.
Federated Learning Based on Dynamic Regularization [link]Paper   link   bibtex  
Task2Sim : Towards Effective Pre-training and Transfer from Synthetic Data. Mishra, S.; Panda, R.; Phoo, C. P.; Chen, C.; Karlinsky, L.; Saenko, K.; Saligrama, V.; and Feris, R. S. CoRR, abs/2112.00054. 2021.
Task2Sim : Towards Effective Pre-training and Transfer from Synthetic Data [link]Paper   link   bibtex  
  2020 (19)
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. Ma, Y.; Olshevsky, A.; Szepesvári, C.; and Saligrama, V. J. Mach. Learn. Res., 21: 133:1–133:36. 2020.
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers [link]Paper   link   bibtex  
Zero Shot Detection. Zhu, P.; Wang, H.; and Saligrama, V. IEEE Trans. Circuits Syst. Video Technol., 30(4): 998–1010. 2020.
Zero Shot Detection [link]Paper   doi   link   bibtex   2 downloads  
Minimax Rank-}1{}1{ Matrix Factorization. Saligrama, V.; Olshevsky, A.; and Hendrickx, J. M. In The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], pages 3426–3436, 2020.
Minimax Rank-$}1{$ Matrix Factorization [link]Paper   link   bibtex  
Budget Learning via Bracketing. Acar, D. A. E.; Gangrade, A.; and Saligrama, V. In The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], pages 4109–4119, 2020.
Budget Learning via Bracketing [link]Paper   link   bibtex  
Don't Even Look Once: Synthesizing Features for Zero-Shot Detection. Zhu, P.; Wang, H.; and Saligrama, V. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020, Seattle, WA, USA, June 13-19, 2020, pages 11690–11699, 2020.
Don't Even Look Once: Synthesizing Features for Zero-Shot Detection [link]Paper   doi   link   bibtex   1 download  
RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?. Kag, A.; Zhang, Z.; and Saligrama, V. In 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020, 2020.
RNNs Incrementally Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? [link]Paper   link   bibtex   1 download  
Minimax Rate for Learning From Pairwise Comparisons in the BTL Model. Hendrickx, J. M.; Olshevsky, A.; and Saligrama, V. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, pages 4193–4202, 2020.
Minimax Rate for Learning From Pairwise Comparisons in the BTL Model [link]Paper   link   bibtex  
Piecewise Linear Regression via a Difference of Convex Functions. Siahkamari, A.; Gangrade, A.; Kulis, B.; and Saligrama, V. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, pages 8895–8904, 2020.
Piecewise Linear Regression via a Difference of Convex Functions [link]Paper   link   bibtex  
Low Dimensional Visual Attributes: An Interpretable Image Encoding. Zhu, P.; Zhu, R.; Mishra, S.; and Saligrama, V. In Pattern Recognition. ICPR International Workshops and Challenges - Virtual Event, January 10-15, 2021, Proceedings, Part III, pages 90–102, 2020.
Low Dimensional Visual Attributes: An Interpretable Image Encoding [link]Paper   doi   link   bibtex  
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm. Yue, Y.; Li, M.; Saligrama, V.; and Zhang, Z. In 25th International Conference on Pattern Recognition, ICPR 2020, Virtual Event / Milan, Italy, January 10-15, 2021, pages 10532–10539, 2020.
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm [link]Paper   doi   link   bibtex  
Limits on Testing Structural Changes in Ising Models. Gangrade, A.; Nazer, B.; and Saligrama, V. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020.
Limits on Testing Structural Changes in Ising Models [link]Paper   link   bibtex  
Learning to Approximate a Bregman Divergence. Siahkamari, A.; Xia, X.; Saligrama, V.; Castañón, D. A.; and Kulis, B. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020.
Learning to Approximate a Bregman Divergence [link]Paper   link   bibtex  
Online Algorithm for Unsupervised Sequential Selection with Contextual Information. Verma, A.; Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020.
Online Algorithm for Unsupervised Sequential Selection with Contextual Information [link]Paper   link   bibtex   6 downloads  
Budget Learning via Bracketing. Gangrade, A.; Acar, D. A. E.; and Saligrama, V. CoRR, abs/2004.06298. 2020.
Budget Learning via Bracketing [link]Paper   link   bibtex   1 download  
Piecewise Linear Regression via a Difference of Convex Functions. Siahkamari, A.; Gangrade, A.; Kulis, B.; and Saligrama, V. CoRR, abs/2007.02422. 2020.
Piecewise Linear Regression via a Difference of Convex Functions [link]Paper   link   bibtex  
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm. Yue, Y.; Li, M.; Saligrama, V.; and Zhang, Z. CoRR, abs/2010.05397. 2020.
RNN Training along Locally Optimal Trajectories via Frank-Wolfe Algorithm [link]Paper   link   bibtex  
Selective Classification via One-Sided Prediction. Gangrade, A.; Kag, A.; and Saligrama, V. CoRR, abs/2010.07853. 2020.
Selective Classification via One-Sided Prediction [link]Paper   link   bibtex  
Online Algorithm for Unsupervised Sequential Selection with Contextual Information. Verma, A.; Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. CoRR, abs/2010.12353. 2020.
Online Algorithm for Unsupervised Sequential Selection with Contextual Information [link]Paper   link   bibtex   6 downloads  
Limits on Testing Structural Changes in Ising Models. Gangrade, A.; Nazer, B.; and Saligrama, V. CoRR, abs/2011.03678. 2020.
Limits on Testing Structural Changes in Ising Models [link]Paper   link   bibtex  
  2019 (18)
Probabilistic Semantic Retrieval for Surveillance Videos With Activity Graphs. Chen, Y.; Wang, J.; Bai, Y.; Castañón, G. D.; and Saligrama, V. IEEE Trans. Multim., 21(3): 704–716. 2019.
Probabilistic Semantic Retrieval for Surveillance Videos With Activity Graphs [link]Paper   doi   link   bibtex  
Cost aware Inference for IoT Devices. Zhu, P.; Acar, D. A. E.; Feng, N.; Jain, P.; and Saligrama, V. In The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan, pages 2770–2779, 2019.
Cost aware Inference for IoT Devices [link]Paper   link   bibtex  
Online Algorithm for Unsupervised Sensor Selection. Verma, A.; Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. In The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan, pages 3168–3176, 2019.
Online Algorithm for Unsupervised Sensor Selection [link]Paper   link   bibtex  
Generalized Zero-Shot Recognition Based on Visually Semantic Embedding. Zhu, P.; Wang, H.; and Saligrama, V. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019, pages 2995–3003, 2019.
Generalized Zero-Shot Recognition Based on Visually Semantic Embedding [link]Paper   doi   link   bibtex  
Robust Text Classifier on Test-Time Budgets. Parvez, M. R.; Bolukbasi, T.; Chang, K.; and Saligrama, V. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019, Hong Kong, China, November 3-7, 2019, pages 1167–1172, 2019.
Robust Text Classifier on Test-Time Budgets [link]Paper   doi   link   bibtex   1 download  
Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations. Wang, H.; Saligrama, V.; Sclaroff, S.; and Ablavsky, V. In 2019 IEEE/CVF International Conference on Computer Vision, ICCV 2019, Seoul, Korea (South), October 27 - November 2, 2019, pages 1252–1261, 2019.
Cost-Aware Fine-Grained Recognition for IoTs Based on Sequential Fixations [link]Paper   doi   link   bibtex   1 download  
Graph Resistance and Learning from Pairwise Comparisons. Hendrickx, J. M.; Olshevsky, A.; and Saligrama, V. In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, pages 2702–2711, 2019.
Graph Resistance and Learning from Pairwise Comparisons [link]Paper   link   bibtex  
Learning Classifiers for Target Domain with Limited or No Labels. Zhu, P.; Wang, H.; and Saligrama, V. In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, pages 7643–7653, 2019.
Learning Classifiers for Target Domain with Limited or No Labels [link]Paper   link   bibtex  
Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models. Gangrade, A.; Venkatesh, P.; Nazer, B.; and Saligrama, V. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, pages 10364–10375, 2019.
Efficient Near-Optimal Testing of Community Changes in Balanced Stochastic Block Models [link]Paper   link   bibtex  
Shallow RNN: Accurate Time-series Classification on Resource Constrained Devices. Dennis, D. K.; Acar, D. A. E.; Mandikal, V.; Sadasivan, V. S.; Saligrama, V.; Simhadri, H. V.; and Jain, P. In Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, pages 12896–12906, 2019.
Shallow RNN: Accurate Time-series Classification on Resource Constrained Devices [link]Paper   link   bibtex  
Online Algorithm for Unsupervised Sensor Selection. Verma, A.; Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. CoRR, abs/1901.04676. 2019.
Online Algorithm for Unsupervised Sensor Selection [link]Paper   link   bibtex  
Learning for New Visual Environments with Limited Labels. Zhu, P.; Wang, H.; and Saligrama, V. CoRR, abs/1901.09079. 2019.
Learning for New Visual Environments with Limited Labels [link]Paper   link   bibtex  
Graph Resistance and Learning from Pairwise Comparisons. Hendrickx, J. M.; Olshevsky, A.; and Saligrama, V. CoRR, abs/1902.00141. 2019.
Graph Resistance and Learning from Pairwise Comparisons [link]Paper   link   bibtex  
Equilibrated Recurrent Neural Network: Neuronal Time-Delayed Self-Feedback Improves Accuracy and Stability. Zhang, Z.; Kag, A.; Sullivan, A.; and Saligrama, V. CoRR, abs/1903.00755. 2019.
Equilibrated Recurrent Neural Network: Neuronal Time-Delayed Self-Feedback Improves Accuracy and Stability [link]Paper   link   bibtex  
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. Ma, Y.; Olshevsky, A.; Saligrama, V.; and Szepesvári, C. CoRR, abs/1904.11608. 2019.
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers [link]Paper   link   bibtex  
Learning Bregman Divergences. Siahkamari, A.; Saligrama, V.; Castanon, D.; and Kulis, B. CoRR, abs/1905.11545. 2019.
Learning Bregman Divergences [link]Paper   link   bibtex  
RNNs Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients?. Kag, A.; Zhang, Z.; and Saligrama, V. CoRR, abs/1908.08574. 2019.
RNNs Evolving on an Equilibrium Manifold: A Panacea for Vanishing and Exploding Gradients? [link]Paper   link   bibtex  
Dont Even Look Once: Synthesizing Features for Zero-Shot Detection. Zhu, P.; Wang, H.; and Saligrama, V. CoRR, abs/1911.07933. 2019.
Dont Even Look Once: Synthesizing Features for Zero-Shot Detection [link]Paper   link   bibtex  
  2018 (8)
Sequential Optimization for Efficient High-Quality Object Proposal Generation. Zhang, Z.; Liu, Y.; Chen, X.; Zhu, Y.; Cheng, M.; Saligrama, V.; and Torr, P. H. S. IEEE Trans. Pattern Anal. Mach. Intell., 40(5): 1209–1223. 2018.
Sequential Optimization for Efficient High-Quality Object Proposal Generation [link]Paper   doi   link   bibtex  
On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems. Somekh-Baruch, A.; Leshem, A.; and Saligrama, V. IEEE Trans. Inf. Theory, 64(8): 5549–5554. 2018.
On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems [link]Paper   doi   link   bibtex  
Two-Sample Testing can be as Hard as Structure Learning in Ising Models: Minimax Lower Bounds. Gangrade, A.; Nazer, B.; and Saligrama, V. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2018, Calgary, AB, Canada, April 15-20, 2018, pages 6931–6935, 2018.
Two-Sample Testing can be as Hard as Structure Learning in Ising Models: Minimax Lower Bounds [link]Paper   doi   link   bibtex  
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers. Ma, Y.; Olshevsky, A.; Szepesvári, C.; and Saligrama, V. In Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018, pages 3341–3350, 2018.
Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers [link]Paper   link   bibtex   3 downloads  
Zero-Shot Detection. Zhu, P.; Wang, H.; Bolukbasi, T.; and Saligrama, V. CoRR, abs/1803.07113. 2018.
Zero-Shot Detection [link]Paper   link   bibtex  
Learning Where to Fixate on Foveated Images. Wang, H.; Saligrama, V.; Sclaroff, S.; and Ablavsky, V. CoRR, abs/1811.06868. 2018.
Learning Where to Fixate on Foveated Images [link]Paper   link   bibtex  
Generalized Zero-Shot Recognition based on Visually Semantic Embedding. Zhu, P.; Wang, H.; and Saligrama, V. CoRR, abs/1811.07993. 2018.
Generalized Zero-Shot Recognition based on Visually Semantic Embedding [link]Paper   link   bibtex  
Testing Changes in Communities for the Stochastic Block Model. Gangrade, A.; Venkatesh, P.; Nazer, B.; and Saligrama, V. CoRR, abs/1812.00769. 2018.
Testing Changes in Communities for the Stochastic Block Model [link]Paper   link   bibtex  
  2017 (20)
PRISM: Person Reidentification via Structured Matching. Zhang, Z.; and Saligrama, V. IEEE Trans. Circuits Syst. Video Technol., 27(3): 499–512. 2017.
PRISM: Person Reidentification via Structured Matching [link]Paper   doi   link   bibtex  
Sparse Signal Processing With Linear and Nonlinear Observations: A Unified Shannon-Theoretic Approach. Aksoylar, C.; Atia, G. K.; and Saligrama, V. IEEE Trans. Inf. Theory, 63(2): 749–776. 2017.
Sparse Signal Processing With Linear and Nonlinear Observations: A Unified Shannon-Theoretic Approach [link]Paper   doi   link   bibtex  
Learning Immune-Defectives Graph Through Group Tests. Ganesan, A.; Jaggi, S.; and Saligrama, V. IEEE Trans. Inf. Theory, 63(5): 3010–3028. 2017.
Learning Immune-Defectives Graph Through Group Tests [link]Paper   doi   link   bibtex  
Comments on the Proof of Adaptive Stochastic Set Cover Based on Adaptive Submodularity and Its Implications for the Group Identification Problem in "Group-Based Active Query Selection for Rapid Diagnosis in Time-Critical Situations". Nan, F.; and Saligrama, V. IEEE Trans. Inf. Theory, 63(11): 7612–7614. 2017.
Comments on the Proof of Adaptive Stochastic Set Cover Based on Adaptive Submodularity and Its Implications for the Group Identification Problem in "Group-Based Active Query Selection for Rapid Diagnosis in Time-Critical Situations" [link]Paper   doi   link   bibtex  
Clustering and Community Detection With Imbalanced Clusters. Aksoylar, C.; Qian, J.; and Saligrama, V. IEEE Trans. Signal Inf. Process. over Networks, 3(1): 61–76. 2017.
Clustering and Community Detection With Imbalanced Clusters [link]Paper   doi   link   bibtex  
Resource Constrained Structured Prediction. Bolukbasi, T.; Chang, K.; Wang, J.; and Saligrama, V. In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA, pages 1756–1762, 2017.
Resource Constrained Structured Prediction [link]Paper   doi   link   bibtex  
Unsupervised Sequential Sensor Acquisition. Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA, pages 803–811, 2017.
Unsupervised Sequential Sensor Acquisition [link]Paper   link   bibtex  
Lower bounds for two-sample structural change detection in ising and Gaussian models. Gangrade, A.; Nazer, B.; and Saligrama, V. In 55th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2017, Monticello, IL, USA, October 3-6, 2017, pages 1016–1025, 2017.
Lower bounds for two-sample structural change detection in ising and Gaussian models [link]Paper   doi   link   bibtex  
Connected Subgraph Detection with Mirror Descent on SDPs. Aksoylar, C.; Orecchia, L.; and Saligrama, V. In Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, pages 51–59, 2017.
Connected Subgraph Detection with Mirror Descent on SDPs [link]Paper   link   bibtex  
Adaptive Neural Networks for Efficient Inference. Bolukbasi, T.; Wang, J.; Dekel, O.; and Saligrama, V. In Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, pages 527–536, 2017.
Adaptive Neural Networks for Efficient Inference [link]Paper   link   bibtex  
Adaptive Classification for Prediction Under a Budget. Nan, F.; and Saligrama, V. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA, pages 4727–4737, 2017.
Adaptive Classification for Prediction Under a Budget [link]Paper   link   bibtex  
Adaptive Neural Networks for Fast Test-Time Prediction. Bolukbasi, T.; Wang, J.; Dekel, O.; and Saligrama, V. CoRR, abs/1702.07811. 2017.
Adaptive Neural Networks for Fast Test-Time Prediction [link]Paper   link   bibtex  
Field of Groves: An Energy-Efficient Random Forest. Takhirov, Z.; Wang, J.; Louis, M. S.; Saligrama, V.; and Joshi, A. CoRR, abs/1704.02978. 2017.
Field of Groves: An Energy-Efficient Random Forest [link]Paper   link   bibtex  
Dynamic Model Selection for Prediction Under a Budget. Nan, F.; and Saligrama, V. CoRR, abs/1704.07505. 2017.
Dynamic Model Selection for Prediction Under a Budget [link]Paper   link   bibtex  
Comments on the proof of adaptive submodular function minimization. Nan, F.; and Saligrama, V. CoRR, abs/1705.03771. 2017.
Comments on the proof of adaptive submodular function minimization [link]Paper   link   bibtex  
Adaptive Classification for Prediction Under a Budget. Nan, F.; and Saligrama, V. CoRR, abs/1705.10194. 2017.
Adaptive Classification for Prediction Under a Budget [link]Paper   link   bibtex  
Sequential Dynamic Decision Making with Deep Neural Nets on a Test-Time Budget. Zhu, H.; Nan, F.; Paschalidis, I. C.; and Saligrama, V. CoRR, abs/1705.10924. 2017.
Sequential Dynamic Decision Making with Deep Neural Nets on a Test-Time Budget [link]Paper   link   bibtex  
Crowdsourcing with Sparsely Interacting Workers. Ma, Y.; Olshevsky, A.; Saligrama, V.; and Szepesvári, C. CoRR, abs/1706.06660. 2017.
Crowdsourcing with Sparsely Interacting Workers [link]Paper   link   bibtex  
Lower Bounds for Two-Sample Structural Change Detection in Ising and Gaussian Models. Gangrade, A.; Nazer, B.; and Saligrama, V. CoRR, abs/1710.10366. 2017.
Lower Bounds for Two-Sample Structural Change Detection in Ising and Gaussian Models [link]Paper   link   bibtex  
Probabilistic Semantic Retrieval for Surveillance Videos with Activity Graphs. Chen, Y.; Wang, J.; Bai, Y.; Castañón, G. D.; and Saligrama, V. CoRR, abs/1712.06204. 2017.
Probabilistic Semantic Retrieval for Surveillance Videos with Activity Graphs [link]Paper   link   bibtex  
  2016 (22)
A Provably Efficient Algorithm for Separable Topic Discovery. Ding, W.; Ishwar, P.; and Saligrama, V. IEEE J. Sel. Top. Signal Process., 10(4): 712–725. 2016.
A Provably Efficient Algorithm for Separable Topic Discovery [link]Paper   doi   link   bibtex  
Retrieval in Long-Surveillance Videos Using User-Described Motion and Object Attributes. Castañón, G.; Elgharib, M. A.; Saligrama, V.; and Jodoin, P. IEEE Trans. Circuits Syst. Video Technol., 26(12): 2313–2327. 2016.
Retrieval in Long-Surveillance Videos Using User-Described Motion and Object Attributes [link]Paper   doi   link   bibtex  
Guest Editorial Inference and Learning over Networks. Matta, V.; Richard, C.; Saligrama, V.; and Sayed, A. H. IEEE Trans. Signal Inf. Process. over Networks, 2(4): 423–425. 2016.
Guest Editorial Inference and Learning over Networks [link]Paper   doi   link   bibtex  
Minimax Optimal Sparse Signal Recovery With Poisson Statistics. Rohban, M. H.; Saligrama, V.; and Vaziri, D. M. IEEE Trans. Signal Process., 64(13): 3495–3508. 2016.
Minimax Optimal Sparse Signal Recovery With Poisson Statistics [link]Paper   doi   link   bibtex  
A multi-resolution approach for discovery and 3-D modeling of archaeological sites using satellite imagery and a UAV-borne camera. Ding, H.; Cristofalo, E.; Wang, J.; Castañón, D. A.; Montijano, E.; Saligrama, V.; and Schwager, M. In 2016 American Control Conference, ACC 2016, Boston, MA, USA, July 6-8, 2016, pages 1359–1365, 2016.
A multi-resolution approach for discovery and 3-D modeling of archaeological sites using satellite imagery and a UAV-borne camera [link]Paper   doi   link   bibtex  
Efficient Training of Very Deep Neural Networks for Supervised Hashing. Zhang, Z.; Chen, Y.; and Saligrama, V. In 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, June 27-30, 2016, pages 1487–1495, 2016.
Efficient Training of Very Deep Neural Networks for Supervised Hashing [link]Paper   doi   link   bibtex  
Zero-Shot Learning via Joint Latent Similarity Embedding. Zhang, Z.; and Saligrama, V. In 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, June 27-30, 2016, pages 6034–6042, 2016.
Zero-Shot Learning via Joint Latent Similarity Embedding [link]Paper   doi   link   bibtex  
Zero-Shot Recognition via Structured Prediction. Zhang, Z.; and Saligrama, V. In Computer Vision - ECCV 2016 - 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VII, pages 533–548, 2016.
Zero-Shot Recognition via Structured Prediction [link]Paper   doi   link   bibtex  
Efficient algorithms for linear polyhedral bandits. Hanawal, M. K.; Leshem, A.; and Saligrama, V. In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016, Shanghai, China, March 20-25, 2016, pages 4796–4800, 2016.
Efficient algorithms for linear polyhedral bandits [link]Paper   doi   link   bibtex  
Energy-Efficient Adaptive Classifier Design for Mobile Systems. Takhirov, Z.; Wang, J.; Saligrama, V.; and Joshi, A. In Proceedings of the 2016 International Symposium on Low Power Electronics and Design, ISLPED 2016, San Francisco Airport, CA, USA, August 08 - 10, 2016, pages 52–57, 2016.
Energy-Efficient Adaptive Classifier Design for Mobile Systems [link]Paper   doi   link   bibtex  
Pruning Random Forests for Prediction on a Budget. Nan, F.; Wang, J.; and Saligrama, V. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 2334–2342, 2016.
Pruning Random Forests for Prediction on a Budget [link]Paper   link   bibtex  
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. Bolukbasi, T.; Chang, K.; Zou, J. Y.; Saligrama, V.; and Kalai, A. T. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 4349–4357, 2016.
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings [link]Paper   link   bibtex   2 downloads  
Optimally Pruning Decision Tree Ensembles With Feature Cost. Nan, F.; Wang, J.; and Saligrama, V. CoRR, abs/1601.00955. 2016.
Optimally Pruning Decision Tree Ensembles With Feature Cost [link]Paper   link   bibtex  
Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs. Root, J.; Saligrama, V.; and Qian, J. CoRR, abs/1601.06105. 2016.
Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs [link]Paper   link   bibtex  
Structured Prediction with Test-time Budget Constraints. Bolukbasi, T.; Chang, K.; Wang, J.; and Saligrama, V. CoRR, abs/1602.08761. 2016.
Structured Prediction with Test-time Budget Constraints [link]Paper   link   bibtex  
Pruning Random Forests for Prediction on a Budget. Nan, F.; Wang, J.; and Saligrama, V. CoRR, abs/1606.05060. 2016.
Pruning Random Forests for Prediction on a Budget [link]Paper   link   bibtex  
Quantifying and Reducing Stereotypes in Word Embeddings. Bolukbasi, T.; Chang, K.; Zou, J. Y.; Saligrama, V.; and Kalai, A. T. CoRR, abs/1606.06121. 2016.
Quantifying and Reducing Stereotypes in Word Embeddings [link]Paper   link   bibtex  
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings. Bolukbasi, T.; Chang, K.; Zou, J. Y.; Saligrama, V.; and Kalai, A. CoRR, abs/1607.06520. 2016.
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings [link]Paper   link   bibtex   2 downloads  
Clustering and Community Detection with Imbalanced Clusters. Aksoylar, C.; Qian, J.; and Saligrama, V. CoRR, abs/1608.07605. 2016.
Clustering and Community Detection with Imbalanced Clusters [link]Paper   link   bibtex  
On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems. Somekh-Baruch, A.; Leshem, A.; and Saligrama, V. CoRR, abs/1609.07415. 2016.
On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems [link]Paper   link   bibtex  
Sequential Learning without Feedback. Hanawal, M. K.; Szepesvári, C.; and Saligrama, V. CoRR, abs/1610.05394. 2016.
Sequential Learning without Feedback [link]Paper   link   bibtex  
Learning Joint Feature Adaptation for Zero-Shot Recognition. Zhang, Z.; and Saligrama, V. CoRR, abs/1611.07593. 2016.
Learning Joint Feature Adaptation for Zero-Shot Recognition [link]Paper   link   bibtex  
  2015 (32)
Prediction of hospitalization due to heart diseases by supervised learning methods. Dai, W.; Brisimi, T. S.; Adams, W. G.; Mela, T.; Saligrama, V.; and Paschalidis, I. C. Int. J. Medical Informatics, 84(3): 189–197. 2015.
Prediction of hospitalization due to heart diseases by supervised learning methods [link]Paper   doi   link   bibtex  
Correction to "Boolean Compressed Sensing and Noisy Group Testing". Atia, G. K.; Saligrama, V.; and Aksoylar, C. IEEE Trans. Inf. Theory, 61(3): 1507. 2015.
Correction to "Boolean Compressed Sensing and Noisy Group Testing" [link]Paper   doi   link   bibtex  
A Topic Modeling Approach to Ranking. Ding, W.; Ishwar, P.; and Saligrama, V. In Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2015, San Diego, California, USA, May 9-12, 2015, 2015.
A Topic Modeling Approach to Ranking [link]Paper   link   bibtex  
Learning Efficient Anomaly Detectors from K-NN Graphs. Root, J.; Qian, J.; and Saligrama, V. In Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2015, San Diego, California, USA, May 9-12, 2015, 2015.
Learning Efficient Anomaly Detectors from K-NN Graphs [link]Paper   link   bibtex  
Cost effective algorithms for spectral bandits. Hanawal, M. K.; and Saligrama, V. In 53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015, Allerton Park & Retreat Center, Monticello, IL, USA, September 29 - October 2, 2015, pages 1323–1329, 2015.
Cost effective algorithms for spectral bandits [link]Paper   doi   link   bibtex  
Rapid: Rapidly accelerated proximal gradient algorithms for convex minimization. Zhang, Z.; and Saligrama, V. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015, South Brisbane, Queensland, Australia, April 19-24, 2015, pages 3796–3800, 2015.
Rapid: Rapidly accelerated proximal gradient algorithms for convex minimization [link]Paper   doi   link   bibtex  
Learning shared rankings from mixtures of noisy pairwise comparisons. Ding, W.; Ishwar, P.; and Saligrama, V. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015, South Brisbane, Queensland, Australia, April 19-24, 2015, pages 5446–5450, 2015.
Learning shared rankings from mixtures of noisy pairwise comparisons [link]Paper   doi   link   bibtex  
Efficient detection and localization on graph structured data. Hanawal, M. K.; and Saligrama, V. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2015, South Brisbane, Queensland, Australia, April 19-24, 2015, pages 5590–5594, 2015.
Efficient detection and localization on graph structured data [link]Paper   doi   link   bibtex  
Group Membership Prediction. Zhang, Z.; Chen, Y.; and Saligrama, V. In 2015 IEEE International Conference on Computer Vision, ICCV 2015, Santiago, Chile, December 7-13, 2015, pages 3916–3924, 2015.
Group Membership Prediction [link]Paper   doi   link   bibtex  
Zero-Shot Learning via Semantic Similarity Embedding. Zhang, Z.; and Saligrama, V. In 2015 IEEE International Conference on Computer Vision, ICCV 2015, Santiago, Chile, December 7-13, 2015, pages 4166–4174, 2015.
Zero-Shot Learning via Semantic Similarity Embedding [link]Paper   doi   link   bibtex  
Feature-Budgeted Random Forest. Nan, F.; Wang, J.; and Saligrama, V. In Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015, pages 1983–1991, 2015.
Feature-Budgeted Random Forest [link]Paper   link   bibtex  
Cheap Bandits. Hanawal, M. K.; Saligrama, V.; Valko, M.; and Munos, R. In Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015, pages 2133–2142, 2015.
Cheap Bandits [link]Paper   link   bibtex  
Learning immune-defectives graph through group tests. Ganesan, A.; Jaggi, S.; and Saligrama, V. In IEEE International Symposium on Information Theory, ISIT 2015, Hong Kong, China, June 14-19, 2015, pages 66–70, 2015.
Learning immune-defectives graph through group tests [link]Paper   doi   link   bibtex   1 download  
Most large topic models are approximately separable. Ding, W.; Ishwar, P.; and Saligrama, V. In 2015 Information Theory and Applications Workshop, ITA 2015, San Diego, CA, USA, February 1-6, 2015, pages 199–203, 2015.
Most large topic models are approximately separable [link]Paper   doi   link   bibtex  
Non-adaptive group testing with inhibitors. Ganesan, A.; Jaggi, S.; and Saligrama, V. In 2015 IEEE Information Theory Workshop, ITW 2015, Jerusalem, Israel, April 26 - May 1, 2015, pages 1–5, 2015.
Non-adaptive group testing with inhibitors [link]Paper   doi   link   bibtex  
Efficient Activity Retrieval through Semantic Graph Queries. Castañón, G. D.; Chen, Y.; Zhang, Z.; and Saligrama, V. In Proceedings of the 23rd Annual ACM Conference on Multimedia Conference, MM '15, Brisbane, Australia, October 26 - 30, 2015, pages 391–400, 2015.
Efficient Activity Retrieval through Semantic Graph Queries [link]Paper   doi   link   bibtex  
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction. Wang, J.; Trapeznikov, K.; and Saligrama, V. In Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada, pages 2152–2160, 2015.
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction [link]Paper   link   bibtex   1 download  
Max-Cost Discrete Function Evaluation Problem under a Budget. Nan, F.; Wang, J.; and Saligrama, V. CoRR, abs/1501.02702. 2015.
Max-Cost Discrete Function Evaluation Problem under a Budget [link]Paper   link   bibtex   1 download  
Learning Efficient Anomaly Detectors from K-NN Graphs. Qian, J.; Root, J.; and Saligrama, V. CoRR, abs/1502.01783. 2015.
Learning Efficient Anomaly Detectors from K-NN Graphs [link]Paper   link   bibtex  
Feature-Budgeted Random Forest. Nan, F.; Wang, J.; and Saligrama, V. CoRR, abs/1502.05925. 2015.
Feature-Budgeted Random Forest [link]Paper   link   bibtex  
Learning Immune-Defectives Graph through Group Tests. Ganesan, A.; Jaggi, S.; and Saligrama, V. CoRR, abs/1503.00555. 2015.
Learning Immune-Defectives Graph through Group Tests [link]Paper   link   bibtex   1 download  
Learning Mixed Membership Mallows Models from Pairwise Comparisons. Ding, W.; Ishwar, P.; and Saligrama, V. CoRR, abs/1504.00757. 2015.
Learning Mixed Membership Mallows Models from Pairwise Comparisons [link]Paper   link   bibtex  
Cheap Bandits. Hanawal, M. K.; Saligrama, V.; Valko, M.; and Munos, R. CoRR, abs/1506.04782. 2015.
Cheap Bandits [link]Paper   link   bibtex  
Necessary and Sufficient Conditions and a Provably Efficient Algorithm for Separable Topic Discovery. Ding, W.; Ishwar, P.; and Saligrama, V. CoRR, abs/1508.05565. 2015.
Necessary and Sufficient Conditions and a Provably Efficient Algorithm for Separable Topic Discovery [link]Paper   link   bibtex  
Sensor Selection by Linear Programming. Wang, J.; Trapeznikov, K.; and Saligrama, V. CoRR, abs/1509.02954. 2015.
Sensor Selection by Linear Programming [link]Paper   link   bibtex  
Zero-Shot Learning via Semantic Similarity Embedding. Zhang, Z.; and Saligrama, V. CoRR, abs/1509.04767. 2015.
Zero-Shot Learning via Semantic Similarity Embedding [link]Paper   link   bibtex  
Group Membership Prediction. Zhang, Z.; Chen, Y.; and Saligrama, V. CoRR, abs/1509.04783. 2015.
Group Membership Prediction [link]Paper   link   bibtex  
Algorithms for Linear Bandits on Polyhedral Sets. Hanawal, M. K.; Leshem, A.; and Saligrama, V. CoRR, abs/1509.07927. 2015.
Algorithms for Linear Bandits on Polyhedral Sets [link]Paper   link   bibtex  
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction. Wang, J.; Trapeznikov, K.; and Saligrama, V. CoRR, abs/1510.07609. 2015.
Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction [link]Paper   link   bibtex   1 download  
BING++: A Fast High Quality Object Proposal Generator at 100fps. Zhang, Z.; Liu, Y.; Bolukbasi, T.; Cheng, M.; and Saligrama, V. CoRR, abs/1511.04511. 2015.
BING++: A Fast High Quality Object Proposal Generator at 100fps [link]Paper   link   bibtex  
Classifying Unseen Instances by Learning Class-Independent Similarity Functions. Zhang, Z.; and Saligrama, V. CoRR, abs/1511.04512. 2015.
Classifying Unseen Instances by Learning Class-Independent Similarity Functions [link]Paper   link   bibtex  
Supervised Hashing with Deep Neural Networks. Zhang, Z.; Chen, Y.; and Saligrama, V. CoRR, abs/1511.04524. 2015.
Supervised Hashing with Deep Neural Networks [link]Paper   link   bibtex  
  2014 (22)
Non-Adaptive Group Testing: Explicit Bounds and Novel Algorithms. Chan, C. L.; Jaggi, S.; Saligrama, V.; and Agnihotri, S. IEEE Trans. Inf. Theory, 60(5): 3019–3035. 2014.
Non-Adaptive Group Testing: Explicit Bounds and Novel Algorithms [link]Paper   doi   link   bibtex  
Information-Theoretic Characterization of Sparse Recovery. Aksoylar, C.; and Saligrama, V. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014, pages 38–46, 2014.
Information-Theoretic Characterization of Sparse Recovery [link]Paper   link   bibtex  
Efficient Distributed Topic Modeling with Provable Guarantees. Ding, W.; Rohban, M. H.; Ishwar, P.; and Saligrama, V. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014, pages 167–175, 2014.
Efficient Distributed Topic Modeling with Provable Guarantees [link]Paper   link   bibtex  
Connected Sub-graph Detection. Qian, J.; Saligrama, V.; and Chen, Y. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014, pages 796–804, 2014.
Connected Sub-graph Detection [link]Paper   link   bibtex  
An LP for Sequential Learning Under Budgets. Wang, J.; Trapeznikov, K.; and Saligrama, V. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, AISTATS 2014, Reykjavik, Iceland, April 22-25, 2014, pages 987–995, 2014.
An LP for Sequential Learning Under Budgets [link]Paper   link   bibtex  
A Novel Visual Word Co-occurrence Model for Person Re-identification. Zhang, Z.; Chen, Y.; and Saligrama, V. In Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part III, pages 122–133, 2014.
A Novel Visual Word Co-occurrence Model for Person Re-identification [link]Paper   doi   link   bibtex  
Model Selection by Linear Programming. Wang, J.; Bolukbasi, T.; Trapeznikov, K.; and Saligrama, V. In Computer Vision - ECCV 2014 - 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part II, pages 647–662, 2014.
Model Selection by Linear Programming [link]Paper   doi   link   bibtex  
Sensing-aware kernel SVM. Ding, W.; Ishwar, P.; Saligrama, V.; and Karl, W. C. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, pages 2947–2951, 2014.
Sensing-aware kernel SVM [link]Paper   doi   link   bibtex  
Fast margin-based cost-sensitive classification. Nan, F.; Wang, J.; Trapeznikov, K.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, pages 2952–2956, 2014.
Fast margin-based cost-sensitive classification [link]Paper   doi   link   bibtex  
Spectral clustering with imbalanced data. Qian, J.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, pages 3057–3061, 2014.
Spectral clustering with imbalanced data [link]Paper   doi   link   bibtex  
Anomalous cluster detection. Qian, J.; Saligrama, V.; and Chen, Y. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, pages 3854–3858, 2014.
Anomalous cluster detection [link]Paper   doi   link   bibtex  
Sparse signal recovery under poisson statistics for online marketing applications. Motamedvaziri, D.; Rohban, M. H.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014, Florence, Italy, May 4-9, 2014, pages 4953–4957, 2014.
Sparse signal recovery under poisson statistics for online marketing applications [link]Paper   doi   link   bibtex  
Information-theoretic bounds for adaptive sparse recovery. Aksoylar, C.; and Saligrama, V. In 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29 - July 4, 2014, pages 1311–1315, 2014.
Information-theoretic bounds for adaptive sparse recovery [link]Paper   doi   link   bibtex  
Efficient Minimax Signal Detection on Graphs. Qian, J.; and Saligrama, V. In Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada, pages 2708–2716, 2014.
Efficient Minimax Signal Detection on Graphs [link]Paper   link   bibtex  
Information-Theoretic Bounds for Adaptive Sparse Recovery. Aksoylar, C.; and Saligrama, V. CoRR, abs/1402.5731. 2014.
Information-Theoretic Bounds for Adaptive Sparse Recovery [link]Paper   link   bibtex  
Sparse Recovery with Linear and Nonlinear Observations: Dependent and Noisy Data. Aksoylar, C.; and Saligrama, V. CoRR, abs/1403.3109. 2014.
Sparse Recovery with Linear and Nonlinear Observations: Dependent and Noisy Data [link]Paper   link   bibtex  
Retrieval in Long Surveillance Videos using User Described Motion and Object Attributes. Castañón, G.; Elgharib, M. A.; Saligrama, V.; and Jodoin, P. CoRR, abs/1405.0234. 2014.
Retrieval in Long Surveillance Videos using User Described Motion and Object Attributes [link]Paper   link   bibtex  
Person Re-identification via Structured Prediction. Zhang, Z.; and Saligrama, V. CoRR, abs/1406.4444. 2014.
Person Re-identification via Structured Prediction [link]Paper   link   bibtex  
RAPID: Rapidly Accelerated Proximal Gradient Algorithms for Convex Minimization. Zhang, Z.; and Saligrama, V. CoRR, abs/1406.4445. 2014.
RAPID: Rapidly Accelerated Proximal Gradient Algorithms for Convex Minimization [link]Paper   link   bibtex  
A Novel Visual Word Co-occurrence Model for Person Re-identification. Zhang, Z.; Chen, Y.; and Saligrama, V. CoRR, abs/1410.6532. 2014.
A Novel Visual Word Co-occurrence Model for Person Re-identification [link]Paper   link   bibtex  
Non-Adaptive Group Testing with Inhibitors. Ganesan, A.; Ebrahimi, J.; Jaggi, S.; and Saligrama, V. CoRR, abs/1410.8440. 2014.
Non-Adaptive Group Testing with Inhibitors [link]Paper   link   bibtex  
A Topic Modeling Approach to Ranking. Ding, W.; Ishwar, P.; and Saligrama, V. CoRR, abs/1412.3705. 2014.
A Topic Modeling Approach to Ranking [link]Paper   link   bibtex  
  2013 (20)
Introduction to the issue on anomalous pattern discovery for spatial, temporal, networked, and high-dimensional signals. Saligrama, V.; Arias-Castro, E.; Chellappa, R.; III, A. O. H.; Nowak, R. D.; and Veeravalli, V. V. IEEE J. Sel. Top. Signal Process., 7(1): 1–3. 2013.
Introduction to the issue on anomalous pattern discovery for spatial, temporal, networked, and high-dimensional signals [link]Paper   doi   link   bibtex  
Multi-stage classifier design. Trapeznikov, K.; Saligrama, V.; and Castañón, D. A. Mach. Learn., 92(2-3): 479–502. 2013.
Multi-stage classifier design [link]Paper   doi   link   bibtex  
Locally-Linear Learning Machines (L3M). Wang, J.; and Saligrama, V. In Asian Conference on Machine Learning, ACML 2013, Canberra, ACT, Australia, November 13-15, 2013, pages 451–466, 2013.
Locally-Linear Learning Machines (L3M) [link]Paper   link   bibtex  
Dynamic topic discovery through sequential projections. Ding, W.; Ishwar, P.; and Saligrama, V. In 2013 Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA, November 3-6, 2013, pages 1100–1104, 2013.
Dynamic topic discovery through sequential projections [link]Paper   doi   link   bibtex  
Supervised Sequential Classification Under Budget Constraints. Trapeznikov, K.; and Saligrama, V. In Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2013, Scottsdale, AZ, USA, April 29 - May 1, 2013, pages 581–589, 2013.
Supervised Sequential Classification Under Budget Constraints [link]Paper   link   bibtex  
Sparse signal recovery under Poisson statistics. Motamedvaziri, D.; Rohban, M. H.; and Saligrama, V. In 51st Annual Allerton Conference on Communication, Control, and Computing, Allerton 2013, Allerton Park & Retreat Center, Monticello, IL, USA, October 2-4, 2013, pages 1450–1457, 2013.
Sparse signal recovery under Poisson statistics [link]Paper   doi   link   bibtex  
Online local linear classification. Wang, J.; Trapeznikov, K.; and Saligrama, V. In 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013, St. Martin, France, December 15-18, 2013, pages 173–176, 2013.
Online local linear classification [link]Paper   doi   link   bibtex  
User-assisted reflection detection and feature point tracking. Elgharib, M. A.; Pitié, F.; Kokaram, A. C.; and Saligrama, V. In Conference on Visual Media Production 2013, CVMP '13, London, United Kingdom, November 6-7, 2013, pages 13:1–13:10, 2013.
User-assisted reflection detection and feature point tracking [link]Paper   doi   link   bibtex  
A new one-class SVM for anomaly detection. Chen, Y.; Qian, J.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2013, Vancouver, BC, Canada, May 26-31, 2013, pages 3567–3571, 2013.
A new one-class SVM for anomaly detection [link]Paper   doi   link   bibtex  
Compressive sensing bounds through a unifying framework for sparse models. Aksoylar, C.; Atia, G. K.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2013, Vancouver, BC, Canada, May 26-31, 2013, pages 5524–5528, 2013.
Compressive sensing bounds through a unifying framework for sparse models [link]Paper   doi   link   bibtex  
A new geometric approach to latent topic modeling and discovery. Ding, W.; Rohban, M. H.; Ishwar, P.; and Saligrama, V. In IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2013, Vancouver, BC, Canada, May 26-31, 2013, pages 5568–5572, 2013.
A new geometric approach to latent topic modeling and discovery [link]Paper   doi   link   bibtex  
Topic Discovery through Data Dependent and Random Projections. Ding, W.; Rohban, M. H.; Ishwar, P.; and Saligrama, V. In Proceedings of the 30th International Conference on Machine Learning, ICML 2013, Atlanta, GA, USA, 16-21 June 2013, pages 1202–1210, 2013.
Topic Discovery through Data Dependent and Random Projections [link]Paper   link   bibtex  
Sparse signal processing with linear and non-linear observations: A unified shannon theoretic approach. Aksoylar, C.; Atia, G. K.; and Saligrama, V. In 2013 IEEE Information Theory Workshop, ITW 2013, Sevilla, Spain, September 9-13, 2013, pages 1–5, 2013.
Sparse signal processing with linear and non-linear observations: A unified shannon theoretic approach [link]Paper   doi   link   bibtex  
Stochastic threshold group testing. Chan, C. L.; Cai, S.; Bakshi, M.; Jaggi, S.; and Saligrama, V. In 2013 IEEE Information Theory Workshop, ITW 2013, Sevilla, Spain, September 9-13, 2013, pages 1–5, 2013.
Stochastic threshold group testing [link]Paper   doi   link   bibtex  
An impossibility result for high dimensional supervised learning. Rohban, M. H.; Ishwar, P.; Orten, B.; Karl, W. C.; and Saligrama, V. In 2013 IEEE Information Theory Workshop, ITW 2013, Sevilla, Spain, September 9-13, 2013, pages 1–5, 2013.
An impossibility result for high dimensional supervised learning [link]Paper   doi   link   bibtex  
Topic Discovery through Data Dependent and Random Projections. Ding, W.; Rohban, M. H.; Ishwar, P.; and Saligrama, V. CoRR, abs/1303.3664. 2013.
Topic Discovery through Data Dependent and Random Projections [link]Paper   link   bibtex  
Sparse Signal Processing with Linear and Non-Linear Observations: A Unified Shannon Theoretic Approach. Aksoylar, C.; Atia, G. K.; and Saligrama, V. CoRR, abs/1304.0682. 2013.
Sparse Signal Processing with Linear and Non-Linear Observations: A Unified Shannon Theoretic Approach [link]Paper   link   bibtex  
Near-Optimal Stochastic Threshold Group Testing. Chan, C. L.; Cai, S.; Bakshi, M.; Jaggi, S.; and Saligrama, V. CoRR, abs/1304.6027. 2013.
Near-Optimal Stochastic Threshold Group Testing [link]Paper   link   bibtex  
Necessary and Sufficient Conditions for Novel Word Detection in Separable Topic Models. Ding, W.; Ishwar, P.; Rohban, M. H.; and Saligrama, V. CoRR, abs/1310.7994. 2013.
Necessary and Sufficient Conditions for Novel Word Detection in Separable Topic Models [link]Paper   link   bibtex  
Sensing-Aware Kernel SVM. Ding, W.; Ishwar, P.; Saligrama, V.; and Karl, W. C. CoRR, abs/1312.0512. 2013.
Sensing-Aware Kernel SVM [link]Paper   link   bibtex  
  2012 (20)
Behavior Subtraction. Jodoin, P.; Saligrama, V.; and Konrad, J. IEEE Trans. Image Process., 21(9): 4244–4255. 2012.
Behavior Subtraction [link]Paper   doi   link   bibtex  
Graph-Constrained Group Testing. Cheraghchi, M.; Karbasi, A.; Mohajer, S.; and Saligrama, V. IEEE Trans. Inf. Theory, 58(1): 248–262. 2012.
Graph-Constrained Group Testing [link]Paper   doi   link   bibtex   1 download  
Boolean Compressed Sensing and Noisy Group Testing. Atia, G. K.; and Saligrama, V. IEEE Trans. Inf. Theory, 58(3): 1880–1901. 2012.
Boolean Compressed Sensing and Noisy Group Testing [link]Paper   doi   link   bibtex  
Aperiodic Sequences With Uniformly Decaying Correlations With Applications to Compressed Sensing and System Identification. Saligrama, V. IEEE Trans. Inf. Theory, 58(9): 6023–6036. 2012.
Aperiodic Sequences With Uniformly Decaying Correlations With Applications to Compressed Sensing and System Identification [link]Paper   doi   link   bibtex  
Real-Time Activity Search of Surveillance Video. Castañón, G.; Saligrama, V.; Caron, A.; and Jodoin, P. In Ninth IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2012, Beijing, China, September 18-21, 2012, pages 246–251, 2012.
Real-Time Activity Search of Surveillance Video [link]Paper   doi   link   bibtex  
Bayesian filtering without an observation model. Jones, P. B.; Mitter, S. K.; and Saligrama, V. In Proceedings of the 51th IEEE Conference on Decision and Control, CDC 2012, December 10-13, 2012, Maui, HI, USA, pages 3496–3501, 2012.
Bayesian filtering without an observation model [link]Paper   doi   link   bibtex  
Video anomaly detection based on local statistical aggregates. Saligrama, V.; and Chen, Z. In 2012 IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, USA, June 16-21, 2012, pages 2112–2119, 2012.
Video anomaly detection based on local statistical aggregates [link]Paper   doi   link   bibtex  
Non-adaptive group testing: Explicit bounds and novel algorithms. Chan, C. L.; Jaggi, S.; Saligrama, V.; and Agnihotri, S. In Proceedings of the 2012 IEEE International Symposium on Information Theory, ISIT 2012, Cambridge, MA, USA, July 1-6, 2012, pages 1837–1841, 2012.
Non-adaptive group testing: Explicit bounds and novel algorithms [link]Paper   doi   link   bibtex  
Exploratory search of long surveillance videos. Castañón, G. D.; Caron, A.; Saligrama, V.; and Jodoin, P. In Proceedings of the 20th ACM Multimedia Conference, MM '12, Nara, Japan, October 29 - November 02, 2012, pages 309–318, 2012.
Exploratory search of long surveillance videos [link]Paper   doi   link   bibtex  
Local Supervised Learning through Space Partitioning. Wang, J.; and Saligrama, V. In Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States, pages 91–99, 2012.
Local Supervised Learning through Space Partitioning [link]Paper   link   bibtex  
Sample complexity of salient feature identification for sparse signal processing. Aksoylar, C.; Atia, G. K.; and Saligrama, V. In IEEE Statistical Signal Processing Workshop, SSP 2012, Ann Arbor, MI, USA, August 5-8, 2012, pages 329–332, 2012.
Sample complexity of salient feature identification for sparse signal processing [link]Paper   doi   link   bibtex  
New statistic in P-value estimation for anomaly detection. Qian, J.; and Saligrama, V. In IEEE Statistical Signal Processing Workshop, SSP 2012, Ann Arbor, MI, USA, August 5-8, 2012, pages 393–396, 2012.
New statistic in P-value estimation for anomaly detection [link]Paper   doi   link   bibtex  
Sensing aware dimensionality reduction for nearest neighbor classification of high dimensional signals. Sun, Z.; Karl, W. C.; Ishwar, P.; and Saligrama, V. In IEEE Statistical Signal Processing Workshop, SSP 2012, Ann Arbor, MI, USA, August 5-8, 2012, pages 405–408, 2012.
Sensing aware dimensionality reduction for nearest neighbor classification of high dimensional signals [link]Paper   doi   link   bibtex  
A combined approach to multi-label multi-task learning. Motamedvaziri, D.; Saligrama, V.; and Castañón, D. A. In IEEE Statistical Signal Processing Workshop, SSP 2012, Ann Arbor, MI, USA, August 5-8, 2012, pages 616–619, 2012.
A combined approach to multi-label multi-task learning [link]Paper   doi   link   bibtex  
Two stage decision system. Trapeznikov, K.; Saligrama, V.; and Castañón, D. A. In IEEE Statistical Signal Processing Workshop, SSP 2012, Ann Arbor, MI, USA, August 5-8, 2012, pages 920–923, 2012.
Two stage decision system [link]Paper   doi   link   bibtex  
Multi-Stage Classifier Design. Trapeznikov, K.; Saligrama, V.; and Castañón, D. A. In Proceedings of the 4th Asian Conference on Machine Learning, ACML 2012, Singapore, Singapore, November 4-6, 2012, pages 459–474, 2012.
Multi-Stage Classifier Design [link]Paper   link   bibtex  
Local Anomaly Detection. Saligrama, V.; and Zhao, M. In Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2012, La Palma, Canary Islands, Spain, April 21-23, 2012, pages 969–983, 2012.
Local Anomaly Detection [link]Paper   link   bibtex  
Non-adaptive Group Testing: Explicit bounds and novel algorithms. Chan, C. L.; Jaggi, S.; Saligrama, V.; and Agnihotri, S. CoRR, abs/1202.0206. 2012.
Non-adaptive Group Testing: Explicit bounds and novel algorithms [link]Paper   link   bibtex  
Graph-based Learning with Unbalanced Clusters. Qian, J.; Saligrama, V.; and Zhao, M. CoRR, abs/1205.1496. 2012.
Graph-based Learning with Unbalanced Clusters [link]Paper   link   bibtex  
Cost Sensitive Sequential Classification. Trapeznikov, K.; Saligrama, V.; and Castañón, D. A. CoRR, abs/1205.4377. 2012.
Cost Sensitive Sequential Classification [link]Paper   link   bibtex  
  2011 (11)
A Token-Based Approach for Distributed Computation in Sensor Networks. Saligrama, V.; and Alanyali, M. IEEE J. Sel. Top. Signal Process., 5(4): 817–832. 2011.
A Token-Based Approach for Distributed Computation in Sensor Networks [link]Paper   doi   link   bibtex  
Abnormality detection using low-level co-occurring events. Benezeth, Y.; Jodoin, P.; and Saligrama, V. Pattern Recognit. Lett., 32(3): 423–431. 2011.
Abnormality detection using low-level co-occurring events [link]Paper   doi   link   bibtex  
Thresholded Basis Pursuit: LP Algorithm for Order-Wise Optimal Support Recovery for Sparse and Approximately Sparse Signals From Noisy Random Measurements. Saligrama, V.; and Zhao, M. IEEE Trans. Inf. Theory, 57(3): 1567–1586. 2011.
Thresholded Basis Pursuit: LP Algorithm for Order-Wise Optimal Support Recovery for Sparse and Approximately Sparse Signals From Noisy Random Measurements [link]Paper   doi   link   bibtex  
Broadband Dispersion Extraction Using Simultaneous Sparse Penalization. Aeron, S.; Bose, S.; Valero, H.; and Saligrama, V. IEEE Trans. Signal Process., 59(10): 4821–4837. 2011.
Broadband Dispersion Extraction Using Simultaneous Sparse Penalization [link]Paper   doi   link   bibtex  
Structural similarity and distance in learning. Wang, J.; Saligrama, V.; and Castañón, D. A. In 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011, Allerton Park & Retreat Center, Monticello, IL, USA, 28-30 September, 2011, pages 744–751, 2011.
Structural similarity and distance in learning [link]Paper   doi   link   bibtex  
Sensing structure in learning-based binary classification of high-dimensional data. Orten, B.; Ishwar, P.; Karl, W. C.; and Saligrama, V. In 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011, Allerton Park & Retreat Center, Monticello, IL, USA, 28-30 September, 2011, pages 1521–1528, 2011.
Sensing structure in learning-based binary classification of high-dimensional data [link]Paper   doi   link   bibtex  
Non-adaptive probabilistic group testing with noisy measurements: Near-optimal bounds with efficient algorithms. Chan, C. L.; Che, P. H.; Jaggi, S.; and Saligrama, V. In 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011, Allerton Park & Retreat Center, Monticello, IL, USA, 28-30 September, 2011, pages 1832–1839, 2011.
Non-adaptive probabilistic group testing with noisy measurements: Near-optimal bounds with efficient algorithms [link]Paper   doi   link   bibtex  
Sensing-aware classification with high-dimensional data. Orten, B.; Ishwar, P.; Karl, W. C.; Saligrama, V.; and Pien, H. H. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, May 22-27, 2011, Prague Congress Center, Prague, Czech Republic, pages 3700–3703, 2011.
Sensing-aware classification with high-dimensional data [link]Paper   doi   link   bibtex  
Active Boosted Learning (ActBoost). Trapeznikov, K.; Saligrama, V.; and Castañón, D. A. In Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2011, Fort Lauderdale, USA, April 11-13, 2011, pages 743–751, 2011.
Active Boosted Learning (ActBoost) [pdf]Paper   link   bibtex  
A Token Based Algorithm to Distributed Computation in Sensor Networks. Saligrama, V.; and Alanyali, M. CoRR, abs/1103.2289. 2011.
A Token Based Algorithm to Distributed Computation in Sensor Networks [link]Paper   link   bibtex  
Non-adaptive probabilistic group testing with noisy measurements: Near-optimal bounds with efficient algorithms. Chan, C. L.; Che, P. H.; Jaggi, S.; and Saligrama, V. CoRR, abs/1107.4540. 2011.
Non-adaptive probabilistic group testing with noisy measurements: Near-optimal bounds with efficient algorithms [link]Paper   link   bibtex  
  2010 (14)
Video Anomaly Identification. Saligrama, V.; Konrad, J.; and Jodoin, P. IEEE Signal Process. Mag., 27(5): 18–33. 2010.
Video Anomaly Identification [link]Paper   doi   link   bibtex  
Activity Based Matching in Distributed Camera Networks. Ermis, E. B.; Clarot, P.; Jodoin, P.; and Saligrama, V. IEEE Trans. Image Process., 19(10): 2595–2613. 2010.
Activity Based Matching in Distributed Camera Networks [link]Paper   doi   link   bibtex  
Information theoretic bounds for compressed sensing. Aeron, S.; Saligrama, V.; and Zhao, M. IEEE Trans. Inf. Theory, 56(10): 5111–5130. 2010.
Information theoretic bounds for compressed sensing [link]Paper   doi   link   bibtex  
Distributed detection in sensor networks with limited range multimodal sensors. Ermis, E. B.; and Saligrama, V. IEEE Trans. Signal Process., 58(2): 843–858. 2010.
Distributed detection in sensor networks with limited range multimodal sensors [link]Paper   doi   link   bibtex  
Markov group testing. Wang, J.; Saligrama, V.; and Castañón, D. A. In 48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010, Monticello, IL, USA, September 29 - October 1, 2020, pages 160–166, 2010.
Markov group testing [link]Paper   doi   link   bibtex  
Decentralized compressive sensing. Motamedvaziri, D.; Saligrama, V.; and Castanon, D. In 48th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2010, Monticello, IL, USA, September 29 - October 1, 2020, pages 607–614, 2010.
Decentralized compressive sensing [link]Paper   doi   link   bibtex  
Noisy filtered sparse processes: Reconstruction and compression. Zhao, M.; and Saligrama, V. In Proceedings of the 49th IEEE Conference on Decision and Control, CDC 2010, December 15-17, 2010, Atlanta, Georgia, USA, pages 2930–2935, 2010.
Noisy filtered sparse processes: Reconstruction and compression [link]Paper   doi   link   bibtex  
Revision of marginal probability assessments. Jones, P. B.; Mitter, S. K.; and Saligrama, V. In 13th Conference on Information Fusion, FUSION 2010, Edinburgh, UK, July 26-29, 2010, pages 1–8, 2010.
Revision of marginal probability assessments [link]Paper   link   bibtex  
A new algorithm for outlier rejection in particle filters. Kumar, R.; Castañón, D. A.; Ermis, E. B.; and Saligrama, V. In 13th Conference on Information Fusion, FUSION 2010, Edinburgh, UK, July 26-29, 2010, pages 1–7, 2010.
A new algorithm for outlier rejection in particle filters [link]Paper   link   bibtex  
Sparsity penalized reconstruction framework for broadband dispersion extraction. Aeron, S.; Bose, S.; Valero, H.; and Saligrama, V. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, 14-19 March 2010, Sheraton Dallas Hotel, Dallas, Texas, USA, pages 2638–2641, 2010.
Sparsity penalized reconstruction framework for broadband dispersion extraction [link]Paper   doi   link   bibtex  
On compressed blind de-convolution of filtered sparse processes. Zhao, M.; and Saligrama, V. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, 14-19 March 2010, Sheraton Dallas Hotel, Dallas, Texas, USA, pages 4038–4041, 2010.
On compressed blind de-convolution of filtered sparse processes [link]Paper   doi   link   bibtex  
Graph-constrained group testing. Cheraghchi, M.; Karbasi, A.; Mohajer, S.; and Saligrama, V. In IEEE International Symposium on Information Theory, ISIT 2010, June 13-18, 2010, Austin, Texas, USA, Proceedings, pages 1913–1917, 2010.
Graph-constrained group testing [link]Paper   doi   link   bibtex  
Probabilistic Belief Revision with Structural Constraints. Jones, P. B.; Saligrama, V.; and Mitter, S. K. In Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, Vancouver, British Columbia, Canada, pages 1036–1044, 2010.
Probabilistic Belief Revision with Structural Constraints [link]Paper   link   bibtex  
Graph-Constrained Group Testing. Cheraghchi, M.; Karbasi, A.; Mohajer, S.; and Saligrama, V. CoRR, abs/1001.1445. 2010.
Graph-Constrained Group Testing [link]Paper   link   bibtex  
  2009 (12)
A technical framework for light- handed regulation of cognitive radios. Sahai, A.; Woyach, K. A.; Atia, G. K.; and Saligrama, V. IEEE Commun. Mag., 47(3): 96–102. 2009.
A technical framework for light- handed regulation of cognitive radios [link]Paper   doi   link   bibtex  
Foreground-Adaptive Background Subtraction. McHugh, J. M.; Konrad, J.; Saligrama, V.; and Jodoin, P. IEEE Signal Process. Lett., 16(5): 390–393. 2009.
Foreground-Adaptive Background Subtraction [link]Paper   doi   link   bibtex  
Noisy group testing: An information theoretic perspective. Atia, G. K.; and Saligrama, V. In 47th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2009, Monticello, IL, USA, September 30 - October 2, 2009, pages 355–362, 2009.
Noisy group testing: An information theoretic perspective [link]Paper   doi   link   bibtex  
Outlier detection via localized p-value estimation. Zhao, M.; and Saligrama, V. In 47th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2009, Monticello, IL, USA, September 30 - October 2, 2009, pages 1482–1489, 2009.
Outlier detection via localized p-value estimation [link]Paper   doi   link   bibtex  
Abnormal events detection based on spatio-temporal co-occurences. Benezeth, Y.; Jodoin, P.; Saligrama, V.; and Rosenberger, C. In 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 20-25 June 2009, Miami, Florida, USA, pages 2458–2465, 2009.
Abnormal events detection based on spatio-temporal co-occurences [link]Paper   doi   link   bibtex  
Unsupervised camera network structure estimation based on activity. Clarot, P.; Ermis, E. B.; Jodoin, P.; and Saligrama, V. In Third ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2009, Como, Italy, August 30 - September 2, 2009, pages 1–8, 2009.
Unsupervised camera network structure estimation based on activity [link]Paper   doi   link   bibtex  
Implicit Active-Contouring with MRF. Jodoin, P.; Saligrama, V.; and Konrad, J. In Image Analysis and Recognition, 6th International Conference, ICIAR 2009, Halifax, Canada, July 6-8, 2009. Proceedings, pages 178–190, 2009.
Implicit Active-Contouring with MRF [link]Paper   doi   link   bibtex  
Anomaly Detection with Score functions based on Nearest Neighbor Graphs. Zhao, M.; and Saligrama, V. In Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, Vancouver, British Columbia, Canada, pages 2250–2258, 2009.
Anomaly Detection with Score functions based on Nearest Neighbor Graphs [link]Paper   link   bibtex  
Boolean Compressed Sensing and Noisy Group Testing. Atia, G. K.; and Saligrama, V. CoRR, abs/0907.1061. 2009.
Boolean Compressed Sensing and Noisy Group Testing [link]Paper   link   bibtex  
Compressed Blind De-convolution. Saligrama, V.; and Zhao, M. CoRR, abs/0910.0239. 2009.
Compressed Blind De-convolution [link]Paper   link   bibtex  
Behavior Subtraction. Jodoin, P.; Saligrama, V.; and Konrad, J. CoRR, abs/0910.2917. 2009.
Behavior Subtraction [link]Paper   link   bibtex  
Anomaly Detection with Score functions based on Nearest Neighbor Graphs. Zhao, M.; and Saligrama, V. CoRR, abs/0910.5461. 2009.
Anomaly Detection with Score functions based on Nearest Neighbor Graphs [link]Paper   link   bibtex  
  2008 (14)
Efficient Sensor Management Policies for Distributed Target Tracking in Multihop Sensor Networks. Aeron, S.; Saligrama, V.; and Castañón, D. A. IEEE Trans. Signal Process., 56(6): 2562–2574. 2008.
Efficient Sensor Management Policies for Distributed Target Tracking in Multihop Sensor Networks [link]Paper   doi   link   bibtex  
One-Bit Distributed Sensing and Coding for Field Estimation in Sensor Networks. Wang, Y.; Ishwar, P.; and Saligrama, V. IEEE Trans. Signal Process., 56(9): 4433–4445. 2008.
One-Bit Distributed Sensing and Coding for Field Estimation in Sensor Networks [link]Paper   doi   link   bibtex  
Codes to unmask spectrum violators in cognitive radio systems. Atia, G. K.; Saligrama, V.; and Sahai, A. In 42nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2008, Pacific Grove, CA, USA, October 26-29, 2008, pages 1574–1578, 2008.
Codes to unmask spectrum violators in cognitive radio systems [link]Paper   doi   link   bibtex  
Crime and Punishment for Cognitive Radios. Woyach, K. A.; Sahai, A.; Atia, G. K.; and Saligrama, V. In 46th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2008, Monticello, IL, USA, September 24-26, 2008, pages 236–243, 2008.
Crime and Punishment for Cognitive Radios [link]Paper   doi   link   bibtex  
On Throughput Maximization and Interference Avoidance in Cognitive Radios. Atia, G. K.; Aeron, S.; Ermis, E. B.; and Saligrama, V. In 5th IEEE Consumer Communications and Networking Conference, CCNC 2008, Las Vegas, NV, USA, January 10-12, 2008, pages 963–967, 2008.
On Throughput Maximization and Interference Avoidance in Cognitive Radios [link]Paper   doi   link   bibtex  
Abnormal behavior detection and behavior matching for networked cameras. Ermis, E. B.; Saligrama, V.; Jodoin, P.; and Konrad, J. In 2008 Second ACM/IEEE International Conference on Distributed Smart Cameras, Stanford, CA, USA, September 7-11, 2008, pages 1–10, 2008.
Abnormal behavior detection and behavior matching for networked cameras [link]Paper   doi   link   bibtex  
Modeling background activity for behavior subtraction. Jodoin, P.; Konrad, J.; and Saligrama, V. In 2008 Second ACM/IEEE International Conference on Distributed Smart Cameras, Stanford, CA, USA, September 7-11, 2008, pages 1–10, 2008.
Modeling background activity for behavior subtraction [link]Paper   doi   link   bibtex  
Motion detection with an unstable camera. Jodoin, P.; Konrad, J.; Saligrama, V.; and Veilleux-Gaboury, V. In Proceedings of the International Conference on Image Processing, ICIP 2008, October 12-15, 2008, San Diego, California, USA, pages 229–232, 2008.
Motion detection with an unstable camera [link]Paper   doi   link   bibtex  
Motion segmentation and abnormal behavior detection via behavior clustering. Ermis, E. B.; Saligrama, V.; Jodoin, P.; and Konrad, J. In Proceedings of the International Conference on Image Processing, ICIP 2008, October 12-15, 2008, San Diego, California, USA, pages 769–772, 2008.
Motion segmentation and abnormal behavior detection via behavior clustering [link]Paper   doi   link   bibtex  
Motion detection with false discovery rate control. McHugh, J. M.; Konrad, J.; Saligrama, V.; Jodoin, P.; and Castañón, D. A. In Proceedings of the International Conference on Image Processing, ICIP 2008, October 12-15, 2008, San Diego, California, USA, pages 873–876, 2008.
Motion detection with false discovery rate control [link]Paper   doi   link   bibtex  
Fundamental Limits on Sensing Capacity for Sensor Networks and Compressed Sensing. Aeron, S.; Zhao, M.; and Saligrama, V. CoRR, abs/0804.3439. 2008.
Fundamental Limits on Sensing Capacity for Sensor Networks and Compressed Sensing [link]Paper   link   bibtex  
Deterministic Designs with Deterministic Guarantees: Toeplitz Compressed Sensing Matrices, Sequence Designs and System Identification. Saligrama, V. CoRR, abs/0806.4958. 2008.
Deterministic Designs with Deterministic Guarantees: Toeplitz Compressed Sensing Matrices, Sequence Designs and System Identification [link]Paper   link   bibtex  
Distributed Detection in Sensor Networks with Limited Range Multi-Modal Sensors. Ermis, E. B.; and Saligrama, V. CoRR, abs/0809.1900. 2008.
Distributed Detection in Sensor Networks with Limited Range Multi-Modal Sensors [link]Paper   link   bibtex  
Thresholded Basis Pursuit: Quantizing Linear Programming Solutions for Optimal Support Recovery and Approximation in Compressed Sensing. Saligrama, V.; and Zhao, M. CoRR, abs/0809.4883. 2008.
Thresholded Basis Pursuit: Quantizing Linear Programming Solutions for Optimal Support Recovery and Approximation in Compressed Sensing [link]Paper   link   bibtex  
  2007 (7)
Wireless Ad Hoc Networks: Strategies and Scaling Laws for the Fixed SNR Regime. Aeron, S.; and Saligrama, V. IEEE Trans. Inf. Theory, 53(6): 2044–2059. 2007.
Wireless Ad Hoc Networks: Strategies and Scaling Laws for the Fixed SNR Regime [link]Paper   doi   link   bibtex  
On Optimal Outage in Relay Channels With General Fading Distributions. Atia, G. K.; Sharif, M.; and Saligrama, V. IEEE Trans. Inf. Theory, 53(10): 3786–3797. 2007.
On Optimal Outage in Relay Channels With General Fading Distributions [link]Paper   doi   link   bibtex  
Distributed Tracking in Multihop Sensor Networks With Communication Delays. Rahman, R.; Alanyali, M.; and Saligrama, V. IEEE Trans. Signal Process., 55(9): 4656–4668. 2007.
Distributed Tracking in Multihop Sensor Networks With Communication Delays [link]Paper   doi   link   bibtex  
Robust Distributed Detection with Limited Range Sensors. Ermis, E. B.; and Saligrama, V. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2007, Honolulu, Hawaii, USA, April 15-20, 2007, pages 1009–1012, 2007.
Robust Distributed Detection with Limited Range Sensors [link]Paper   doi   link   bibtex  
On sensing capacity of sensor networks for the class of linear observation, fixed SNR models. Aeron, S.; Zhao, M.; and Saligrama, V. CoRR, abs/0704.3434. 2007.
On sensing capacity of sensor networks for the class of linear observation, fixed SNR models [link]Paper   link   bibtex  
Distributed Detection in Sensor Networks with Limited Range Sensors. Ermis, E. B.; and Saligrama, V. CoRR, abs/cs/0701178. 2007.
Distributed Detection in Sensor Networks with Limited Range Sensors [link]Paper   link   bibtex  
One-bit Distributed Sensing and Coding for Field Estimation in Sensor Networks. Wang, Y.; Ishwar, P.; and Saligrama, V. CoRR, abs/cs/0701196. 2007.
One-bit Distributed Sensing and Coding for Field Estimation in Sensor Networks [link]Paper   link   bibtex  
  2006 (12)
Search and discovery in an uncertain networked world. Ermis, E. B.; Alanyali, M.; and Saligrama, V. IEEE Signal Process. Mag., 23(4): 107–118. 2006.
Search and discovery in an uncertain networked world [link]Paper   doi   link   bibtex  
Energy Efficient Policies for Distributed Target Tracking in Multihop Sensor Networks. Aeron, S.; Saligrama, V.; and Castañón, D. A. In 45th IEEE Conference on Decision and Control, CDC 2006, San Diego, CA, USA, December 13-15, 2006, pages 380–385, 2006.
Energy Efficient Policies for Distributed Target Tracking in Multihop Sensor Networks [link]Paper   doi   link   bibtex  
Reliable Distributed Estimation with Intermittent Communications. Saligrama, V.; and Castañón, D. A. In 45th IEEE Conference on Decision and Control, CDC 2006, San Diego, CA, USA, December 13-15, 2006, pages 6763–6768, 2006.
Reliable Distributed Estimation with Intermittent Communications [link]Paper   doi   link   bibtex  
Randomized Sequential Algorithms for Data Aggregation in Sensor Networks. Savas, O.; Alanyali, M.; and Saligrama, V. In 40th Annual Conference on Information Sciences and Systems, CISS 2006, Princeton, NJ, USA, 22-24 March 2006, pages 165–170, 2006.
Randomized Sequential Algorithms for Data Aggregation in Sensor Networks [link]Paper   doi   link   bibtex  
Detection and Localization in Sensor Networks Using Distributed FDR. Ermis, E. B.; and Saligrama, V. In 40th Annual Conference on Information Sciences and Systems, CISS 2006, Princeton, NJ, USA, 22-24 March 2006, pages 699–704, 2006.
Detection and Localization in Sensor Networks Using Distributed FDR [link]Paper   doi   link   bibtex  
Distributed Target tracking and localization in multi-hop networks. Aeron, S.; Saligrama, V.; and Castanon, D. In 40th Annual Conference on Information Sciences and Systems, CISS 2006, Princeton, NJ, USA, 22-24 March 2006, pages 990–995, 2006.
Distributed Target tracking and localization in multi-hop networks [link]Paper   doi   link   bibtex  
Efficient In-Network Processing Through Local Ad-Hoc Information Coalescence. Savas, O.; Alanyali, M.; and Saligrama, V. In Distributed Computing in Sensor Systems, Second IEEE International Conference, DCOSS 2006, San Francisco, CA, USA, June 18-20, 2006, Proceedings, pages 252–265, 2006.
Efficient In-Network Processing Through Local Ad-Hoc Information Coalescence [link]Paper   doi   link   bibtex  
Effect of Geometry on the Diversity-Multiplexing Tradeoff in Relay Channels. Atia, G. K.; Sharif, M.; and Saligrama, V. In Proceedings of the Global Telecommunications Conference, 2006. GLOBECOM '06, San Francisco, CA, USA, 27 November - 1 December 2006, 2006.
Effect of Geometry on the Diversity-Multiplexing Tradeoff in Relay Channels [link]Paper   doi   link   bibtex  
Reliable Tracking With Intermittent Communications. Saligrama, V.; and Castañón, D. A. In 2006 IEEE International Conference on Acoustics Speech and Signal Processing, ICASSP 2006, Toulouse, France, May 14-19, 2006, pages 1141–1144, 2006.
Reliable Tracking With Intermittent Communications [link]Paper   doi   link   bibtex  
On the macroscopic effects of local interactions in multi-hop wireless networks. Saligrama, V.; and Starobinski, D. In 4th International Symposium on Modeling and Optimization in Mobile, Ad-Hoc and Wireless Networks (WiOpt 2006), 3-6 April 2006, Boston, Massachusetts, USA, pages 161–168, 2006.
On the macroscopic effects of local interactions in multi-hop wireless networks [link]Paper   doi   link   bibtex  
Wireless ad-hoc networks: Strategies and Scaling laws for the fixed SNR regime. Aeron, S.; and Saligrama, V. CoRR, abs/cs/0608089. 2006.
Wireless ad-hoc networks: Strategies and Scaling laws for the fixed SNR regime [link]Paper   link   bibtex  
  2005 (2)
Adaptive statistical sampling methods for decentralized estimation and detection of localized phenomena. Ermis, E. B.; and Saligrama, V. In 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05, Philadelphia, Pennsylvania, USA, March 18-23, 2005, pages 1045–1048, 2005.
Adaptive statistical sampling methods for decentralized estimation and detection of localized phenomena [link]Paper   doi   link   bibtex  
Adaptive statistical sampling methods for decentralized estimation and detection of localized phenomena. Ermis, E. B.; and Saligrama, V. In Proceedings of the Fourth International Symposium on Information Processing in Sensor Networks, IPSN 2005, April 25-27, 2005, UCLA, Los Angeles, California, USA, pages 143–150, 2005.
Adaptive statistical sampling methods for decentralized estimation and detection of localized phenomena [link]Paper   doi   link   bibtex  
  2004 (5)
Necessary and sufficient conditions for robust identification of uncertain LTI systems. Saligrama, V. Syst. Control. Lett., 53(2): 117–125. 2004.
Necessary and sufficient conditions for robust identification of uncertain LTI systems [link]Paper   doi   link   bibtex  
Distributed Bayesian hypothesis testing in sensor networks. Alanyali, M.; Saligrama, V.; Savas, O.; and Aeron, S. In Proceedings of the 2004 American Control Conference, ACC 2004, Boston, MA, USA, June 30 - July 2, 2004, pages 5369–5374, 2004.
Distributed Bayesian hypothesis testing in sensor networks [link]Paper   doi   link   bibtex  
Performance guarantees in sensor networks. Saligrama, V.; Shi, Y.; and Karl, W. C. In 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2004, Montreal, Quebec, Canada, May 17-21, 2004, pages 269–272, 2004.
Performance guarantees in sensor networks [link]Paper   doi   link   bibtex  
Classification in sensor networks. Saligrama, V.; Alanyali, M.; Savas, O.; and Aeron, S. In Proceedings of the 2004 IEEE International Symposium on Information Theory, ISIT 2004, Chicago Downtown Marriott, Chicago, Illinois, USA, June 27 - July 2, 2004, pages 251, 2004.
Classification in sensor networks [link]Paper   doi   link   bibtex  
Capacity scaling in wireless ad-hoc networks with P\mboxe. Aeron, S.; and Saligrama, V. In Proceedings of the 2004 IEEE International Symposium on Information Theory, ISIT 2004, Chicago Downtown Marriott, Chicago, Illinois, USA, June 27 - July 2, 2004, pages 469, 2004.
Capacity scaling in wireless ad-hoc networks with P\(_\mboxe\) [link]Paper   doi   link   bibtex  
  2003 (1)
Identification of uncertain systems described by linear fractional transformations. Saligrama, V. In 42nd IEEE Conference on Decision and Control, CDC 2003, Maui, Hawaii, USA, December 9-12, 2003, pages 5532–5537, 2003.
Identification of uncertain systems described by linear fractional transformations [link]Paper   doi   link   bibtex  
  2001 (1)
Dynamic inverse optimization. Gentry, S.; Saligrama, V.; and Feron, E. In American Control Conference, ACC 2001, Arlington, VA, USA, 25-27 June, 2001, pages 4722–4727, 2001.
Dynamic inverse optimization [link]Paper   doi   link   bibtex  

2018

P. Zhu, H. Wang, V. Saligrama, Zero-shot detection, (pdf)

Y. Ma, A. Olshevsky, C. Szepesvari, V. Saligrama, Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers, (pdf) ICML 2018

Z. Zhang, Y. Liu, X. Chen, Y. Zhu, M-M Cheng, V Saligrama, PHS Torr, Sequential optimization for efficient high-quality object proposal generation, IEEE TPAMI 2018

Y. Chen, J. Wang, Y. Bai, G. Castañón, V. Saligrama, Probabilistic Semantic Retrieval for Surveillance Videos with Activity Graphs, IEEE Transactions on Multimedia, 2018 (pdf)

A. Gangrade, B. Nazer, V. Saligrama, Two-Sample Testing can be as hard as Structure Learning in ISING Models: Minimax Lower Bounds, ICASSP 2018

KR Hansen et. al., Mild Blast Injury Produces Acute Changes in Basal Intracellular Calcium Levels and Activity Patterns in Mouse Hippocampal Neurons, Journal of Neurotrama, 2018

2017

F. Nan, V. Saligrama, Adaptive Classification for Prediction on a Budget, NIPS 2017 (pdf)

T. Bolukbasi, J. Wang, O. Dekel, V. Saligrama, Adaptive Neural Networks for Fast Test-Time Prediction, ICML (2017) (pdf)

C. Aksoylar, L. Orrechia, V. Saligrama, Mirror Descent Approach for Anomalous Subgraph Detection, ICML 2017

F. Nan, V. Saligrama, Dynamic Model Selection for Prediction Under a Budget, Arxiv Preprint (pdf)

M. Hanawal, C. Szepesvari, V. Saligrama, Unsupervised Sensor Selection, AISTATS 2017 (pdf)

T. Bolukbasi, K-W. Chang, J. Wang, V. Saligrama, Resource Constrained Structured Prediction, AAAI 2017

A. Ganesan, S. Jaggi, V. Saligrama, Learning Immune-Defectives Graph through Group Tests, IEEE Trans. on Information Theory, 2017

2016

A. Somekh-Baruch, A. Leshem, V. Saligrama, On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems, (arxiv paper)

E. Arias-Castro, B. Pelletier, V. Saligrama, Remember the Curse of Dimensionality: The Case of Goodness-of-Fit Testing in Arbitrary Dimension, (arxiv paper)

Pruning Random Forests for Prediction on a Budget, NIPS 2016 (paper)

Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings, NIPS 2016 (paper)

Zero-Shot Recognition via Structured Prediction, ECCV 2016 (paper)

Sparse Signal Processing with Linear and Non-Linear Observations: A Unified Shannon Theoretic Approach, IEEE Trans. on Information Theory, 206 (paper)

PRISM: Person Re-Identification via Structured Matching, IEEE TCSVT 2016 (paper)

Clustering and Community Detection with Imbalanced Clusters, IEEE TCSVT, 2016 (paper)

Zero-Shot Learning via Joint Latent Similarity Embedding, CVPR 2016 (poster)

Efficient Training of Very Deep Neural Networks for Supervised Hashing, CVPR 2016 (poster)

Necessary and Sufficient Conditions and a Provably Efficient Algorithm for Separable Topic Discovery, IEEE Journal of Selected Topics in Signal Processing, to appear

Minimax Optimal Sparse Signal Recovery with Poisson Statistics, IEEE Transactions on Signal Processing, May 2016

Efficient Algorithms for Linear Polyhedral Bandits, ICASSP 2016

Structured Prediction with Test-time Budget Constraints, http://arxiv.org/abs/1602.08761

Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs, http://arxiv.org/abs/1601.06105

BING++: A Fast High Quality Object Proposal Generator at 100fps, http://arxiv.org/abs/1511.04511

2015

Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction, NIPS 2015

Group Membership Prediction, ICCV 2015

Zero Shot Recognition via Semantic Label Embedding, ICCV 2015

Zero Shot Activity Retrieval through Semantic Graph Queries, ACM Multi-Media 2015

Retrieval in Long Surveillance Videos using User-Described Motion & Object Attributes, IEEE Transactions on Circuits Systems and Video Technology, to appear

Cheap Bandits, ICML 2015

Feature-Budgeted Random Forest, ICML 2015

Learning Immune Defectives Graph Through Group Tests, ISIT 2015

A Topic Modeling Approach to Ranking, AISTATS 2015

Learning Efficient Anomaly Detectors from K-NN Graphs, AISTATS 2015

Non-Adaptive Group Testing with Inhibitors, ITW 2015

Efficient Detection and Localization on Graph Structured Data, ICASSP 2015

RAPID: Rapidly Accelerated Proximal Gradient Algorithms for Convex Minimization, ICASSP 2015

Learning Shared Rankings From Mixtures of Noisy Pairwise Comparisons, ICASSP 2015

Prediction of Hospitalization due to Heart Diseases by Supervised Learning, Int. Journal of Medical Informatics, March 2015

2014

Efficient Minimax Detection on Graphs, NIPS 2014

A Topic Modeling Approach to Rank Aggregation, NIPS Workshop on Analysis of Ranking Data, (Weicong Ding: Best Student Paper Award).

A Novel Visual Word Co-occurrence Model for Person Re-identification, ECCV Visual Re-ID workshop, 2014

Model Selection by Linear Programming, ECCV 2014

Non-Adaptive Group Testing: Explicit Bounds and Algorithms, IEEE Transactions on Information Theory, May 2014.

Information-Theoretic Bounds for Adaptive Sparse Recovery, ISIT 2014

Information-Theoretic Characterization of Sparse Recovery, AISTATS 2014

An LP for Sequential Learning Under Budgets, AISTATS 2014

Efficient Distributed Topic Modeling with Provable Guarantees, AISTATS 2014

Connected Sub-graph Detection, AISTATS 2014

Sensing-aware kernel SVM, ICASSP 2014

Fast Margin-based Cost-Sensitive Classification, ICASSP 2014

Spectral Clustering with Imbalanced Data, ICASSP 2014

Anomalous Cluster Detection, ICASSP 2014

Sparse Signal Recovery under Poisson Statistics for Online Marketing Applications, ICASSP 2014

 

2013

Local Linear Learning Machines (L3M), (Oral) ACML 2013

An Impossibility Result for High Dimensional Supervised Learning, (arxiv version), ITW 2013

Sparse Signal Processing with Linear and Non-Linear Observations: A Unified Shannon Theoretic Approach, (arxiv preprint)

Near-Optimal Stochastic Threshold Group Testing, (arxiv preprint), ITW 2013

Topic Discovery through Data Dependent and Random Projections, ICML 2013 (Oral)

Multistage Learning under Budget Constraints, AISTATS 2013 (Oral)

Compressive sensing bounds through a unifying framework for sparse models, ICASSP 2013

A New One-Class SVM for Anomaly Detection, ICASSP 2013

A new geometric approach to latent topic modeling and discovery, ICASSP 2013

2012

J. Wang, V. Saligrama, Local Supervised Learning through Space Partitioning, NIPS 2012 (code)

K. Trapeznikov et. al., Multi Stage Classifier Design, ACML 2012

G. Castanon et. al., Exploratory Search of Long Surveillance Videos, (long paper), ACM Multimedia, 2012

P. Jones, S. Mitter, V. Saligrama, Bayesian Filtering without an Observation Model, IEEE Conference on Decision and Control, 2012

P. M. Jodoin, V. Saligrama, J. Konrad, Behavior Subtraction, IEEE Transactions on Image Processing, Sept. 2012/p>

V. Saligrama, Aperiodic Sequences with Uniformly Decaying Correlations with Applications to Compressed Sensing and System Identi cation, IEEE Transactions on Information Theory, Sept 2012.

C. L. Chan, S. Jaggi, V. Saligrama, S. Agnihotri, Non-Adaptive Group Testing: Explicit Bounds and Algorithms, ISIT 2012

V. Saligrama, Z. Chen, Video Anomaly Detection Based on Local Statistical Aggregates, CVPR 2012

V. Saligrama, M. Zhao, Local Anomaly Detection, AISTATS 2012

D. Motamed-Vaziri, V. Saligrama, D. Castanon, A Combined Approach to Multi-label Multi-task Learning, IEEE Statistical Signal Processing Workshop, 2012

C. Aksoylar, G. Atia, V. Saligrama, Sample Complexity of Salient Feature Identification for Sparse Signal Processing, IEEE Statistical Signal Processing Workshop, 2012

B. Orten, W. Karl, P. Ishwar, V. Saligrama, Sensing Aware Dimensionality Reduction for Nearest Neighbor Classification of High Dimensional Signals, IEEE Statistical Signal Processing Workshop, 2012

G. Atia, V. Saligrama, “Boolean Compressed Sensing and Noisy Group Testing,’’ IEEE Trans. on Information Theory, March 2012

M. Cheraghchi, A. Karbasi, S. Mohajer, V. Saligrama, “Graph Constrained Group Testing,’’ IEEE Trans. on Information Theory, Jan 2012

2011

G. Atia, V. Saligrama, A Mutual Information Characterization of Sparse Signal Processing, Allerton UIUC 2011

J. Qian, V. Saligrama, M. Zhao, Graph Construction for Learning with Unbalanced Data, Preprint 2011

J. Wang, V. Saligrama, D. Castanon, Structural Similarity and Distance in Learning, Allerton 2011

B. Orten, P. Ishwar, W. Karl, V. Saligrama, Sensing Structure in Learning-Based Binary Classification of High-Dimensional Data: Opportunities and Perils, Allerton 2011

B. Orten et. al., Sensing-aware classification with high-dimensional data, ICASSP 2011

B. Orten et. al., Sensing Structure in Learning-Based Binary Classification of High-Dimensional Data: Opportunities and Perils, Allerton 2011

C. L. Park et. al., Non-adaptive probabilistic group testing with noisy measurements: Near-optimal bounds with efficient algorithms, Allerton 2011

G. Atia, V. Saligrama, A mutual information characterization of sparse signal processing, ICALPGT 2011

B. Orten et. al., Sensing-aware classification with high-dimensional data, ICASSP 2011

K. Trapeznikov, V. Saligrama, D. Castanon, “Active Boosted Learning,” AISTATS 2011

S. Aeron, S. Bose, H. P. Valero, V. Saligrama, Broadband Dispersion Extraction Using Simultaneous Sparse Penalization, IEEE Transactions on Signal Processing, 2011

V. Saligrama, M. Alanyali, “Token Based Algorithms for Distributed Computation,’’ IEEE Journal of Selected Areas in Signal Processing, Aug. 2011

V. Saligrama, M. Zhao, “Thresholded Basis Pursuit: A Linear Programming Approach to Optimal Support Recovery of Compressed Sparse Signals,’’ IEEE Transactions on Information Theory, March 2011

Y. Benezeth, P. Jodoin, V. Saligrama, “Abnormality Detection Using Low-Level Co-occurring Events,’’ Pattern Recognition Letters, Feb. 2011

2010

P. Jones, V. Saligrama, S. Mitter, Probabilistic Belief Revision with Structural Constraints, NIPS 2010

J. Wang, V. Saligrama, D. Castanon, “Markov and Hidden Markov Model Group Testing,” Allerton UIUC 2010,

D. Motamedvaziri, V. Saligrama, D. Castanon, “Decentralized Compressive Sensing,” Allerton UIUC 2010

P. Jones, S. Mitter, V. Saligrama, “Revision of Marginal Probability Assessments,” Fusion 2010, Edinburgh, UK

R. Kumar, D. Castanon, E. Ermis, V. Saligrama, “A new algorithm for outlier rejection in particle filters,” Fusion 2010, Edinburgh, UK

M. Zhao, V. Saligrama, “ Noisy Filtered Processes: Reconstruction and Compression,” IEEE Conference on Decision and Control, Atlanta, Dec. 2010

M. Zhao, V. Saligrama, “Compressed Blind Deconvolution,’’ ICASSP 2010

M. Cheraghchi, A. Karbasi, S. Mohajer, V. Saligrama, “Graph Constrained Group Testing,’’ ISIT. 2010.

S. Aeron, S. Bose, H.P. Valero, V. Saligrama, “ Sparsity Penalized Reconstruction Framework for Broadband Dispersion Extraction,’’ pages: 2638 – 2641, ICASSP 2010

V. Saligrama, Deterministic Designs with Deterministic Guarantees: Toeplitz Compressed Sensing Matrices, Sequence Designs and System Identification, Submitted to IEEE Transactions on Information Theory.

S. Aeron, V. Saligrama, M. Zhao, “Information Theoretic Analysis for Compressed Sensing,’’ IEEE Trans. on Information Theory, pages: 5111 – 5130, Oct. 2010

E. Ermis, P. Jodoin, V. Saligrama, “Activity Based Matching in Multi-Camera Networks,’’ IEEE Trans. on Image Processing, 2595 – 2613, Oct. 2010.

V. Saligrama, J. Konrad, V. Saligrama, “Video Anomaly Identification,’’ IEEE Signal Processing Magazine, pages: 18-33, Sept. 2010.

E. Ermis, V. Saligrama, “Distributed Detection for Multi-Modal Limited Range Sensors,’’ IEEE Transactions on Signal Processing, pages 843-858, Jan 2010

2009

J. McHugh, J. Konrad, V. Saligrama, and P.-M. Jodoin, “Foreground-adaptive background subtraction,” IEEE Signal Process. Lett., pages 390-393, Sep. 2009.

A. Sahai, K.Woyach, G. Atia, and V. Saligrama, “A technical perspective on light-handed regulation for cognitive radios,” pages 96-102, IEEE Communications Magazine, Jan 2009

M. Zhao, V. Saligrama, “Anomaly Detection with Score Functions on K Nearest Neighbor Graphs,’’ NIPS 2009, (Spotlight Presentation)

G. Atia, V. Saligrama, “Noisy Group Testing: An information theoretic perspective,’’ Allerton, pages, 355 – 362, UIUC 2009

Jodoin P-M, Saligrama V. Konrad J., Implicit Active-Contouring with MRF, International Conference on Image Analysis and Recognition (ICIAR), 2009

Y. Benezeth, P. M. Jodoin, and V. Saligrama, and C. Rosenberger, “Abnormal Events Detection Based on Spatio-Temporal Co-occurences,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVPR), Jun. 2009

E. Ermis, P. Clarot, P. M. Jodoin, and V. Saligrama, “Unsupervised Camera Network Structure Estimation Based on Activity,” in ICDSC 2009

M. Zhao, V. Saligrama, Outlier detection via localized p-value estimation, Allerton 2009