{"id":11,"date":"2014-09-04T14:18:38","date_gmt":"2014-09-04T18:18:38","guid":{"rendered":"https:\/\/sites.bu.edu\/data\/?page_id=11"},"modified":"2020-10-22T17:21:53","modified_gmt":"2020-10-22T21:21:53","slug":"publications","status":"publish","type":"page","link":"https:\/\/sites.bu.edu\/data\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"<h4>I no longer maintain this page. With few exceptions, my papers are first posted on <a href=\"https:\/\/arxiv.org\/search\/cs?searchtype=author&amp;query=Saligrama%2C+V\">arxiv.org<\/a>. You can also find my publications on <a href=\"https:\/\/scholar.google.co.in\/citations?user=S4z3uzMAAAAJ&amp;hl=en\">Google Scholar<\/a><\/h4>\n<p>&nbsp;<\/p>\n<p><script src=\"http:\/\/bibbase.org\/dblp\/venkatesh_saligrama?jsonp=1\"><\/script><\/p>\n<h1>2018<\/h1>\n<p>P. Zhu, H. Wang, V. Saligrama, Zero-shot detection, (<a href=\"https:\/\/arxiv.org\/abs\/1803.07113\">pdf<\/a>)<\/p>\n<p>Y. Ma, A. Olshevsky, C. Szepesvari, V. Saligrama, Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers, (<a href=\"http:\/\/proceedings.mlr.press\/v80\/ma18b.html\">pdf<\/a>) ICML 2018<\/p>\n<p>Z. Zhang, Y. Liu, X. Chen, Y. Zhu, M-M Cheng, V Saligrama, PHS Torr, <a href=\"https:\/\/ieeexplore.ieee.org\/abstract\/document\/7932893\/\" data-clk=\"hl=en&amp;sa=T&amp;ei=3u8iW5nmBoWrmgGNvqLQDQ\">Sequential optimization for efficient high-quality object proposal generation,<\/a> IEEE TPAMI 2018<\/p>\n<div>Y. Chen, J. Wang, Y. Bai, G. Casta\u00f1\u00f3n, V. Saligrama, Probabilistic Semantic Retrieval for Surveillance Videos with Activity Graphs, IEEE Transactions on Multimedia, 2018 (<a href=\"http:\/\/1 Probabilistic Semantic Retrieval for Surveillance Videos with Activity Graphs\">pdf<\/a>)<\/div>\n<p>A. Gangrade, B. Nazer, V. Saligrama, Two-Sample Testing can be as hard as Structure Learning in ISING Models: Minimax Lower Bounds, ICASSP 2018<\/p>\n<p>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<\/p>\n<h1>2017<\/h1>\n<p>F. Nan, V. Saligrama, Adaptive Classification for Prediction on a Budget, NIPS 2017 (<a href=\"https:\/\/arxiv.org\/pdf\/1705.10194.pdf\">pdf<\/a>)<\/p>\n<p>T. Bolukbasi, J. Wang, O. Dekel, V. Saligrama, Adaptive Neural Networks for Fast Test-Time Prediction, ICML (2017) (<a href=\"https:\/\/arxiv.org\/pdf\/1702.07811.pdf\">pdf<\/a>)<\/p>\n<p>C. Aksoylar, L. Orrechia, V. Saligrama, Mirror Descent Approach for Anomalous Subgraph Detection, ICML 2017<\/p>\n<p>F. Nan, V. Saligrama, Dynamic Model Selection for Prediction Under a Budget, Arxiv Preprint (<a href=\"https:\/\/arxiv.org\/pdf\/1704.07505.pdf\">pdf<\/a>)<\/p>\n<p>M. Hanawal, C. Szepesvari, V. Saligrama, Unsupervised Sensor Selection, AISTATS 2017 (<a href=\"https:\/\/arxiv.org\/pdf\/1610.05394.pdf\">pdf<\/a>)<\/p>\n<p class=\"title mathjax\">T. Bolukbasi, K-W. Chang, J. Wang, V. Saligrama, <a href=\"https:\/\/arxiv.org\/abs\/1602.08761\">Resource Constrained Structured Prediction<\/a>, AAAI 2017<\/p>\n<p class=\"title mathjax\">A. Ganesan, S. Jaggi, V. Saligrama, <a href=\"https:\/\/arxiv.org\/abs\/1601.06105\">Learning Immune-Defectives Graph through Group Tests<\/a>, IEEE Trans. on Information Theory, 2017<\/p>\n<h1>2016<\/h1>\n<div class=\"list-title mathjax\">\n<div class=\"list-title mathjax\">\n<p>A. Somekh-Baruch, A. Leshem, V. Saligrama, On the Non-Existence of Unbiased Estimators in Constrained Estimation Problems<a href=\"https:\/\/arxiv.org\/abs\/1609.07415\">, <\/a>(<a href=\"https:\/\/arxiv.org\/abs\/1609.07415\">arxiv paper<\/a>)<\/p>\n<p>E. Arias-Castro, B. Pelletier, V. Saligrama, Remember the Curse of Dimensionality: The Case of Goodness-of-Fit Testing in Arbitrary Dimension, (<a href=\"https:\/\/arxiv.org\/pdf\/1607.08156.pdf\">arxiv paper<\/a>)<\/p>\n<p>Pruning Random Forests for Prediction on a Budget, NIPS 2016 (<a href=\"http:\/\/arxiv.org\/abs\/1606.05060\">paper<\/a>)<\/p>\n<p class=\"title mathjax\">Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings, NIPS 2016 (<a href=\"http:\/\/arxiv.org\/abs\/1607.06520\">paper<\/a>)<\/p>\n<p class=\"title mathjax\">Zero-Shot Recognition via Structured Prediction, ECCV 2016 (<a href=\"https:\/\/zimingzhang.files.wordpress.com\/2014\/10\/1473.pdf\">paper<\/a>)<\/p>\n<p class=\"title mathjax\">Sparse Signal Processing with Linear and Non-Linear Observations: A Unified Shannon Theoretic Approach, IEEE Trans. on Information Theory, 206 (<a href=\"http:\/\/arxiv.org\/abs\/1304.0682\">paper<\/a>)<\/p>\n<p class=\"title mathjax\">PRISM: Person Re-Identi\ufb01cation via Structured Matching, IEEE TCSVT 2016 (<a href=\"https:\/\/zimingzhang.files.wordpress.com\/2014\/10\/tcsvt_reid.pdf\">paper<\/a>)<\/p>\n<p class=\"title mathjax\">Clustering and Community Detection with Imbalanced Clusters, IEEE TCSVT, 2016 (<a href=\"https:\/\/arxiv.org\/abs\/1608.07605\">paper<\/a>)<\/p>\n<p class=\"title mathjax\"><a href=\"http:\/\/www.cv-foundation.org\/openaccess\/content_cvpr_2016\/html\/Zhang_Zero-Shot_Learning_via_CVPR_2016_paper.html\">Zero-Shot Learning via Joint Latent Similarity Embedding<\/a>, CVPR 2016 (<a href=\"\/data\/files\/2016\/07\/CVPR2016_Shared_latent_models_36_48_final.pdf\">poster<\/a>)<\/p>\n<p class=\"title mathjax\"><a href=\"http:\/\/www.cv-foundation.org\/openaccess\/content_cvpr_2016\/html\/Zhang_Efficient_Training_of_CVPR_2016_paper.html\">Efficient Training of Very Deep Neural Networks for Supervised Hashing<\/a>, CVPR 2016 (<a href=\"\/data\/files\/2016\/07\/CVPR2016_Hashing_2016_36_48_final.pdf\">poster<\/a>)<\/p>\n<p class=\"title mathjax\"><a href=\"http:\/\/arxiv.org\/abs\/1508.05565\">Necessary and Sufficient Conditions and a Provably Efficient Algorithm for Separable Topic Discovery<\/a>, IEEE Journal of Selected Topics in Signal Processing, to appear<\/p>\n<p class=\"title mathjax\"><a href=\"http:\/\/arxiv.org\/abs\/1501.05200\">Minimax Optimal Sparse Signal Recovery with Poisson Statistics<\/a>, IEEE Transactions on Signal Processing, May 2016<\/p>\n<p><a href=\"http:\/\/arxiv.org\/abs\/1509.07927\">Efficient Algorithms for Linear Polyhedral Bandits<\/a>, ICASSP 2016<\/p>\n<p class=\"title mathjax\">Structured Prediction with Test-time Budget Constraints, <a href=\"http:\/\/arxiv.org\/abs\/1602.08761\">http:\/\/arxiv.org\/abs\/1602.08761<\/a><\/p>\n<p>Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs, <a href=\"http:\/\/arxiv.org\/abs\/1601.06105\">http:\/\/arxiv.org\/abs\/1601.06105<\/a><\/p>\n<p class=\"title mathjax\">BING++: A Fast High Quality Object Proposal Generator at 100fps, <a href=\"http:\/\/arxiv.org\/abs\/1511.04511\">http:\/\/arxiv.org\/abs\/1511.04511<\/a><\/p>\n<h1>2015<\/h1>\n<p><span><a href=\"https:\/\/papers.nips.cc\/paper\/5982-efficient-learning-by-directed-acyclic-graph-for-resource-constrained-prediction.pdf\">Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction<\/a>, NIPS 2015<\/span><\/p>\n<p><a href=\"http:\/\/arxiv.org\/pdf\/1509.04783v1.pdf\">Group Membership Prediction<\/a>, ICCV 2015<\/p>\n<p><a href=\"http:\/\/arxiv.org\/pdf\/1509.04767.pdf\">Zero Shot Recognition via Semantic Label Embedding<\/a>, ICCV 2015<\/p>\n<p><span id=\"ctl00_cph_paperSummary_gvPaperSummary_ctl02_PaperTitleLabel\"><a href=\"\/data\/files\/2015\/10\/mm15-efficient-activity-retrieval-through-semantic-graph.pdf\">Zero Shot Activity Retrieval through Semantic Graph Queries<\/a>, ACM Multi-Media 2015<br \/>\n<\/span><\/p>\n<p><a href=\"https:\/\/sites.bu.edu\/data\/files\/2015\/06\/retrieval-long-surveillance2.pdf\">Retrieval in Long Surveillance Videos using User-Described Motion &amp; Object Attributes<\/a>, IEEE Transactions on Circuits Systems and Video Technology, to appear<\/p>\n<p><a href=\"http:\/\/jmlr.org\/proceedings\/papers\/v37\/hanawal15.pdf\">Cheap Bandits<\/a>, ICML 2015<\/p>\n<p><a href=\"http:\/\/jmlr.org\/proceedings\/papers\/v37\/nan15.pdf\">Feature-Budgeted Random Forest<\/a>, ICML 2015<br \/>\n<a href=\"http:\/\/arxiv.org\/abs\/1503.00555\"><br \/>\nLearning Immune Defectives Graph Through Group Tests<\/a>, ISIT 2015<\/p>\n<p><a href=\"http:\/\/arxiv.org\/abs\/1412.3705\">A Topic Modeling Approach to Ranking<\/a>, AISTATS 2015<\/p>\n<p><a href=\"http:\/\/arxiv.org\/abs\/1502.01783\">Learning Efficient Anomaly Detectors from K-NN Graphs<\/a>, AISTATS 2015<\/p>\n<p><a href=\"http:\/\/arxiv.org\/abs\/1410.8440\">Non-Adaptive Group Testing with Inhibitors<\/a>, ITW 2015<\/p>\n<p><a href=\"http:\/\/www.bu.edu\/phpbin\/cise\/download.php?tracking_number=2015-CA-0001\">Efficient Detection and Localization on Graph Structured Data<\/a>, ICASSP 2015<\/p>\n<p><a href=\"http:\/\/arxiv.org\/abs\/1406.4445\">RAPID: Rapidly Accelerated Proximal Gradient Algorithms for Convex Minimization<\/a>, ICASSP 2015<\/p>\n<p><a href=\"https:\/\/sites.bu.edu\/data\/files\/2015\/08\/rank_ICASSP_finalversion.pdf\">Learning Shared Rankings From Mixtures of Noisy Pairwise Comparisons<\/a>, ICASSP 2015<\/p>\n<p><a href=\"http:\/\/www.ncbi.nlm.nih.gov\/pubmed\/25497295\">Prediction of Hospitalization due to Heart Diseases by Supervised Learning<\/a>, Int. Journal of Medical Informatics, March 2015<\/p>\n<h1>2014<\/h1>\n<p><a href=\"http:\/\/papers.nips.cc\/paper\/5525-efficient-minimax-signal-detection-on-graphs.pdf\">Efficient Minimax Detection on Graphs<\/a>, NIPS 2014<\/p>\n<div class=\"page\" title=\"Page 1\">\n<div class=\"section\">\n<div class=\"layoutArea\">\n<div class=\"column\">\n<p><a href=\"http:\/\/events.csa.iisc.ernet.in\/NIPS-14-rankingsws\/Papers\/3_A_Topic_Modeling_Approach_To_Rank_Aggregation.pdf\">A Topic Modeling Approach to Rank Aggregation<\/a>, NIPS Workshop on Analysis of Ranking Data, (<strong>Weicong Ding: Best Student Paper Award<\/strong>).<\/p>\n<p><a href=\"http:\/\/arxiv.org\/pdf\/1410.6532.pdf\">A Novel Visual Word Co-occurrence Model for Person Re-identification<\/a>, ECCV Visual Re-ID workshop, 2014<\/p>\n<p><a href=\"http:\/\/vigir.missouri.edu\/~gdesouza\/Research\/Conference_CDs\/ECCV_2014\/papers\/8690\/86900647.pdf\">Model Selection by Linear Programming<\/a>, ECCV 2014<\/p>\n<p><a href=\"https:\/\/sites.bu.edu\/data\/files\/2015\/06\/06763117.pdf\">Non-Adaptive Group Testing: Explicit Bounds and Algorithms<\/a>, IEEE Transactions on Information Theory, May 2014.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p><a href=\"http:\/\/arxiv.org\/pdf\/1402.5731v1.pdf\">Information-Theoretic Bounds for Adaptive Sparse Recovery<\/a>, ISIT 2014<\/p>\n<p><a href=\"http:\/\/jmlr.org\/proceedings\/papers\/v33\/aksoylar14.pdf\">Information-Theoretic Characterization of Sparse Recovery<\/a><b>, <\/b>AISTATS 2014<\/p>\n<p><a href=\"http:\/\/jmlr.org\/proceedings\/papers\/v33\/wang14b.pdf\">An LP for Sequential Learning Under Budgets<\/a>, AISTATS 2014<\/p>\n<p><a href=\"http:\/\/jmlr.org\/proceedings\/papers\/v33\/ding14a.pdf\">Efficient Distributed Topic Modeling with Provable Guarantees<\/a>, AISTATS 2014<\/p>\n<p><a href=\"http:\/\/jmlr.org\/proceedings\/papers\/v33\/qian14.pdf\">Connected Sub-graph Detection<\/a>, AISTATS 2014<\/p>\n<p><a href=\"http:\/\/arxiv.org\/abs\/1312.0512\">Sensing-aware kernel SVM<\/a>, ICASSP 2014<\/p>\n<p><a href=\"http:\/\/ieeexplore.ieee.org\/xpls\/abs_all.jsp?arnumber=6854141&amp;tag=1\">Fast Margin-based Cost-Sensitive Classification<\/a>, ICASSP 2014<\/p>\n<p><a href=\"http:\/\/arxiv.org\/abs\/1302.5134\">Spectral Clustering with Imbalanced Data<\/a>, ICASSP 2014<\/p>\n<p>Anomalous Cluster Detection, ICASSP 2014<\/p>\n<p><a href=\"http:\/\/arxiv.org\/abs\/1307.4666\">Sparse Signal Recovery under Poisson Statistics for Online Marketing Applications<\/a>, ICASSP 2014<\/p>\n<p>&nbsp;<\/p>\n<h1>2013<\/h1>\n<p><a href=\"http:\/\/jmlr.org\/proceedings\/papers\/v29\/Wang13a.pdf\">Local Linear Learning Machines<\/a> (L3M), (Oral) ACML 2013<\/p>\n<p><a href=\"http:\/\/arxiv.org\/abs\/1301.6915\">An Impossibility Result for High Dimensional Supervised Learning<\/a>, (arxiv version), ITW 2013<\/p>\n<p><a href=\"http:\/\/arxiv.org\/abs\/1304.0682\">Sparse Signal Processing with Linear and Non-Linear Observations: A Unified Shannon Theoretic Approach<\/a>, (arxiv preprint)<\/p>\n<p><a href=\"http:\/\/arxiv.org\/pdf\/1304.6027.pdf\">Near-Optimal Stochastic Threshold Group Testing<\/a>, (arxiv preprint), ITW 2013<\/p>\n<p><a href=\"http:\/\/arxiv.org\/pdf\/1303.3664.pdf\">Topic Discovery through Data Dependent and Random Projections<\/a>, ICML 2013 (Oral)<\/p>\n<p><a href=\"http:\/\/blogs.bu.edu\/srv\/files\/2013\/02\/aistats2013_4.pdf\">Multistage Learning under Budget Constraints<\/a>, AISTATS 2013 (Oral)<\/p>\n<p>Compressive sensing bounds through a unifying framework for sparse models, ICASSP 2013<\/p>\n<p>A New One-Class SVM for Anomaly Detection, ICASSP 2013<\/p>\n<p>A new geometric approach to latent topic modeling and discovery, ICASSP 2013<\/p>\n<h1>2012<\/h1>\n<p>J. Wang, V. Saligrama, <a href=\"http:\/\/books.nips.cc\/papers\/files\/nips25\/NIPS2012_0054.pdf\">Local Supervised Learning through Space Partitioning<\/a>, NIPS 2012 (<a href=\"http:\/\/blogs.bu.edu\/joewang\/code\/\">code<\/a>)<\/p>\n<p>K. Trapeznikov et. al., <a href=\"http:\/\/arxiv.org\/abs\/1205.4377\">Multi Stage Classifier Design<\/a>, ACML 2012<\/p>\n<p>G. Castanon et. al., <a href=\"http:\/\/blogs.bu.edu\/srv\/files\/2012\/08\/fp026-castanon.pdf\">Exploratory Search of Long Surveillance Videos<\/a>, (long paper), ACM Multimedia, 2012<\/p>\n<p>P. Jones, S. Mitter, V. Saligrama, Bayesian Filtering without an Observation Model, IEEE Conference on Decision and Control, 2012<\/p>\n<p>P. M. Jodoin, V. Saligrama, J. Konrad, <a href=\"http:\/\/blogs.bu.edu\/srv\/files\/2012\/04\/IEEE_TIP_2011.pdf\">Behavior Subtraction<\/a>, IEEE Transactions on Image Processing, Sept. 2012\/p&gt;<\/p>\n<p>V. Saligrama, <a href=\"http:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?arnumber=6215053\">Aperiodic Sequences with Uniformly Decaying Correlations with Applications to Compressed Sensing and System Identi\fcation, IEEE Transactions on Information Theory<\/a>, Sept 2012.<\/p>\n<p>C. L. Chan, S. Jaggi, V. Saligrama, S. Agnihotri, <a href=\"http:\/\/arxiv.org\/abs\/1202.0206\">Non-Adaptive Group Testing: Explicit Bounds and Algorithms<\/a>, ISIT 2012<\/p>\n<p>V. Saligrama, Z. Chen, <a href=\"http:\/\/blogs.bu.edu\/srv\/files\/2012\/04\/cvpr_final.pdf\">Video Anomaly Detection Based on Local Statistical Aggregates<\/a>, CVPR 2012<\/p>\n<p>V. Saligrama, M. Zhao, <a href=\"http:\/\/www.bu.edu\/phpbin\/cise\/download.php?publication_id=1113\">Local Anomaly Detection<\/a>, AISTATS 2012<\/p>\n<p>D. Motamed-Vaziri, V. Saligrama, D. Castanon, A Combined Approach to Multi-label Multi-task Learning, IEEE Statistical Signal Processing Workshop, 2012<\/p>\n<p>C. Aksoylar, G. Atia, V. Saligrama, Sample Complexity of Salient Feature Identification for Sparse Signal Processing, IEEE Statistical Signal Processing Workshop, 2012<\/p>\n<p>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<\/p>\n<p>G. Atia, V. Saligrama, \u201c<a href=\"http:\/\/arxiv.org\/abs\/0907.1061\">Boolean Compressed Sensing and Noisy Group Testing<\/a>,\u2019\u2019 IEEE Trans. on Information Theory, March 2012<\/p>\n<p>M. Cheraghchi, A. Karbasi, S. Mohajer, V. Saligrama, \u201c<a href=\"http:\/\/arxiv.org\/abs\/1001.1445\">Graph Constrained Group Testing<\/a>,\u2019\u2019 IEEE Trans. on Information Theory, Jan 2012<\/p>\n<h1>2011<\/h1>\n<p>G. Atia, V. Saligrama, <a href=\"http:\/\/www.bu.edu\/phpbin\/cise\/download.php?publication_id=1117\">A Mutual Information Characterization of Sparse Signal Processing<\/a>, Allerton UIUC 2011<\/p>\n<p>J. Qian, V. Saligrama, M. Zhao, <a href=\"http:\/\/arxiv.org\/abs\/1112.2319\">Graph Construction for Learning with Unbalanced Data<\/a>, Preprint 2011<\/p>\n<p>J. Wang, V. Saligrama, D. Castanon, <a href=\"http:\/\/arxiv.org\/PS_cache\/arxiv\/pdf\/1110\/1110.5847v1.pdf\">Structural Similarity and Distance in Learning<\/a>, Allerton 2011<\/p>\n<p>B. Orten, P. Ishwar, W. Karl, V. Saligrama, Sensing Structure in Learning-Based Binary Classification of High-Dimensional Data: Opportunities and Perils, Allerton 2011<\/p>\n<p>B. Orten et. al., <a href=\"http:\/\/www.bu.edu\/phpbin\/cise\/download.php?publication_id=1193\">Sensing-aware classification with high-dimensional data<\/a>, ICASSP 2011<\/p>\n<p>B. Orten et. al., Sensing Structure in Learning-Based Binary Classification of High-Dimensional Data: Opportunities and Perils, Allerton 2011<\/p>\n<p>C. L. Park et. al., <a href=\"http:\/\/arxiv.org\/PS_cache\/arxiv\/pdf\/1107\/1107.4540v1.pdf\">Non-adaptive probabilistic group testing with noisy measurements: Near-optimal bounds with efficient algorithms<\/a>, Allerton 2011<\/p>\n<p>G. Atia, V. Saligrama, A mutual information characterization of sparse signal processing, ICALPGT 2011<\/p>\n<p>B. Orten et. al., Sensing-aware classification with high-dimensional data, ICASSP 2011<\/p>\n<p>K. Trapeznikov, V. Saligrama, D. Castanon, \u201c<a href=\"http:\/\/www.bu.edu\/phpbin\/cise\/download.php?publication_id=1074\">Active Boosted Learning<\/a>,\u201d AISTATS 2011<\/p>\n<p>S. Aeron, S. Bose, H. P. Valero, V. Saligrama, <a href=\"http:\/\/blogs.bu.edu\/srv\/files\/2011\/06\/Broadband.pdf\">Broadband Dispersion Extraction Using Simultaneous Sparse Penalization<\/a>, IEEE Transactions on Signal Processing, 2011<\/p>\n<p>V. Saligrama, M. Alanyali, \u201c<a href=\"http:\/\/www.bu.edu\/phpbin\/cise\/download.php?tracking_number=2010-IR-0010\">Token Based Algorithms for Distributed Computation<\/a>,\u2019\u2019 IEEE Journal of Selected Areas in Signal Processing, Aug. 2011<\/p>\n<p>V. Saligrama, M. Zhao, \u201c<a href=\"http:\/\/arxiv.org\/abs\/0809.4883\">Thresholded Basis Pursuit: A Linear Programming Approach to Optimal Support Recovery of Compressed Sparse Signals<\/a>,\u2019\u2019 IEEE Transactions on Information Theory, March 2011<\/p>\n<p>Y. Benezeth, P. Jodoin, V. Saligrama, \u201c<a href=\"http:\/\/dl.acm.org\/citation.cfm?id=1923007\">Abnormality Detection Using Low-Level Co-occurring Events<\/a>,\u2019\u2019 Pattern Recognition Letters, Feb. 2011<\/p>\n<h1>2010<\/h1>\n<p>P. Jones, V. Saligrama, S. Mitter, <a href=\"http:\/\/books.nips.cc\/papers\/files\/nips23\/NIPS2010_0927.pdf\">Probabilistic Belief Revision with Structural Constraints,<\/a> NIPS 2010<\/p>\n<p>J. Wang, V. Saligrama, D. Castanon, \u201cMarkov and Hidden Markov Model Group Testing,\u201d Allerton UIUC 2010,<\/p>\n<p>D. Motamedvaziri, V. Saligrama, D. Castanon, \u201cDecentralized Compressive Sensing,\u201d Allerton UIUC 2010<\/p>\n<p>P. Jones, S. Mitter, V. Saligrama, \u201cRevision of Marginal Probability Assessments,\u201d Fusion 2010, Edinburgh, UK<\/p>\n<p>R. Kumar, D. Castanon, E. Ermis, V. Saligrama, \u201cA new algorithm for outlier rejection in particle filters,\u201d<strong> <\/strong>Fusion 2010, Edinburgh, UK<\/p>\n<p>M. Zhao, V. Saligrama, \u201c<a href=\"http:\/\/blogs.bu.edu\/srv\/files\/2011\/03\/1894_OL.pdf\"> Noisy Filtered Processes: Reconstruction and Compression<\/a>,\u201d IEEE Conference on Decision and Control, Atlanta, Dec. 2010<\/p>\n<p>M. Zhao, V. Saligrama, \u201cCompressed Blind Deconvolution,\u2019\u2019 ICASSP 2010<\/p>\n<p>M. Cheraghchi, A. Karbasi, S. Mohajer, V. Saligrama, \u201cGraph Constrained Group Testing,\u2019\u2019 ISIT. 2010.<\/p>\n<p>S. Aeron, S. Bose, H.P. Valero, V. Saligrama, \u201c Sparsity Penalized Reconstruction Framework for Broadband Dispersion Extraction,\u2019\u2019 pages: 2638 \u2013 2641, ICASSP 2010<\/p>\n<p>V. Saligrama, <a href=\"http:\/\/arxiv.org\/abs\/0806.4958\">Deterministic Designs with Deterministic Guarantees: Toeplitz Compressed Sensing Matrices, Sequence Designs and System Identification<\/a>, Submitted to IEEE Transactions on Information Theory.<\/p>\n<p>S. Aeron, V. Saligrama, M. Zhao, \u201c<a href=\"http:\/\/arxiv.org\/abs\/0804.3439\">Information Theoretic Analysis for Compressed Sensing<\/a>,\u2019\u2019 IEEE Trans. on Information Theory, pages: 5111 \u2013 5130, Oct. 2010<\/p>\n<p>E. Ermis, P. Jodoin, V. Saligrama, \u201c<a href=\"http:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?arnumber=5484585\">Activity Based Matching in Multi-Camera Networks<\/a>,\u2019\u2019 IEEE Trans. on Image Processing, 2595 \u2013 2613, Oct. 2010.<\/p>\n<p>V. Saligrama, J. Konrad, V. Saligrama, \u201c<a href=\"http:\/\/blogs.bu.edu\/srv\/files\/2011\/04\/05562666.pdf\">Video Anomaly Identification<\/a>,\u2019\u2019 IEEE Signal Processing Magazine, pages: 18-33, Sept. 2010.<\/p>\n<p>E. Ermis, V. Saligrama, \u201c<a href=\"http:\/\/arxiv.org\/abs\/0809.1900\">Distributed Detection for Multi-Modal Limited Range Sensors<\/a>,\u2019\u2019 IEEE Transactions on Signal Processing, pages 843-858, Jan 2010<\/p>\n<h1>2009<\/h1>\n<p>J. McHugh, J. Konrad, V. Saligrama, and P.-M. Jodoin, \u201c<a href=\"http:\/\/ieeexplore.ieee.org\/xpl\/articleDetails.jsp?arnumber=4804946\">Foreground-adaptive background subtraction<\/a>,\u201d IEEE Signal Process. Lett., pages 390-393, Sep. 2009.<\/p>\n<p>A. Sahai, K.Woyach, G. Atia, and V. Saligrama, \u201c<a href=\"http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.152.5944&amp;rep=rep1&amp;type=pdf\">A technical perspective on light-handed regulation for cognitive radios<\/a>,\u201d pages 96-102, IEEE Communications Magazine, Jan 2009<\/p>\n<p>M. Zhao, V. Saligrama, \u201c<a href=\"http:\/\/books.nips.cc\/papers\/files\/nips22\/NIPS2009_0608.pdf\">Anomaly Detection with Score Functions on K Nearest Neighbor Graphs<\/a>,\u2019\u2019 NIPS 2009, (Spotlight Presentation)<\/p>\n<p>G. Atia, V. Saligrama, \u201cNoisy Group Testing: An information theoretic perspective,\u2019\u2019 Allerton, pages, 355 \u2013 362, UIUC 2009<\/p>\n<p>Jodoin P-M, Saligrama V. Konrad J., Implicit Active-Contouring with MRF, International Conference on Image Analysis and Recognition (ICIAR), 2009<\/p>\n<p>Y. Benezeth, P. M. Jodoin, and V. Saligrama, and C. Rosenberger, \u201cAbnormal Events Detection Based on Spatio-Temporal Co-occurences,\u201d in IEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVPR), Jun. 2009<\/p>\n<p>E. Ermis, P. Clarot, P. M. Jodoin, and V. Saligrama, \u201cUnsupervised Camera Network Structure Estimation Based on Activity,\u201d in ICDSC 2009<\/p>\n<p>M. Zhao, V. Saligrama, Outlier detection via localized p-value estimation, Allerton 2009<\/p>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>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 &nbsp; 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 [&hellip;]<\/p>\n","protected":false},"author":9227,"featured_media":0,"parent":0,"menu_order":8,"comment_status":"closed","ping_status":"closed","template":"page-templates\/no-sidebars.php","meta":[],"_links":{"self":[{"href":"https:\/\/sites.bu.edu\/data\/wp-json\/wp\/v2\/pages\/11"}],"collection":[{"href":"https:\/\/sites.bu.edu\/data\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.bu.edu\/data\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/data\/wp-json\/wp\/v2\/users\/9227"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/data\/wp-json\/wp\/v2\/comments?post=11"}],"version-history":[{"count":51,"href":"https:\/\/sites.bu.edu\/data\/wp-json\/wp\/v2\/pages\/11\/revisions"}],"predecessor-version":[{"id":773,"href":"https:\/\/sites.bu.edu\/data\/wp-json\/wp\/v2\/pages\/11\/revisions\/773"}],"wp:attachment":[{"href":"https:\/\/sites.bu.edu\/data\/wp-json\/wp\/v2\/media?parent=11"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}