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Anandkumar, Animashree; Ge, Rong et al. (2017) Analyzing Tensor Power Method Dynamics in Overcomplete Regime Journal of Machine Learning Research; Vol. 18; No. 22;
https://resolver.caltech.edu/CaltechAUTHORS:20170920-110910164
Agarwal, Alekh; Anandkumar, Animashree et al. (2016) Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization SIAM Journal of Optimization; Vol. 26; No. 4;
https://resolver.caltech.edu/CaltechAUTHORS:20170927-090108498
Wang, Yining; Anandkumar, Animashree (2016) Online and Differentially-Private Tensor Decomposition Neural Information Processing Systems 2016; arXiv; Advances in Neural Information Processing Systems 29 (NIPS 2016), 5-10 December 2016 , Barcelona, Spain
https://resolver.caltech.edu/CaltechAUTHORS:20190401-123322786
Shi, Yang; Niranjan, U. N. et al. (2016) Tensor Contractions with Extended BLAS Kernels on CPU and GPU 2016 IEEE 23rd International Conference on High Performance Computing; 2016 IEEE 23rd International Conference on High Performance Computing (HiPC), 19-22 December 2016 , Hyderabad, India
https://resolver.caltech.edu/CaltechAUTHORS:20170920-112945692
Azizzadenesheli, Kamyar; Lazaric, Alessandro et al. (2016) Reinforcement Learning in Rich-Observation MDPs using Spectral Methods arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20190327-085718507
Gitter, Anthony; Huang, Furong et al. (2016) Unsupervised learning of transcriptional regulatory networks via latent tree graphical models arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20190401-123329660
Azizzadenesheli, Kamyar; Lazaric, Alessandro et al. (2016) Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies Proceedings of Machine Learning Research; Vol. 49; Conference on Learning Theory (COLT 2016), 23-26 June 2016 , New York, NY
https://resolver.caltech.edu/CaltechAUTHORS:20190401-123326217
Azizzadenesheli, Kamyar; Lazaric, Alessandro et al. (2016) Reinforcement Learning of POMDPs using Spectral Methods Proceedings of Machine Learning Research; Vol. 49; Conference on Learning Theory (COLT 2016), 23-26 June 2016 , New York, NY
https://resolver.caltech.edu/CaltechAUTHORS:20190401-123310700
Arabshahi, Forough; Anandkumar, Animashree (2016) Spectral Methods for Correlated Topic Models arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20190401-123319347
Sedghi, Hanie; Anandkumar, Anima (2016) Training Input-Output Recurrent Neural Networks through Spectral Methods arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20190401-123315920
Anandkumar, Anima; Ge, Rong (2016) Efficient approaches for escaping higher order saddle points in non-convex optimization arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20190401-123307245
Wang, Yining; Tung, Hsiao-Yu et al. (2015) Fast and Guaranteed Tensor Decomposition via Sketching NIPS'15 Proceedings of the 28th International Conference on Neural Information Processing Systems; arXiv; Vol. 1; 28th International Conference on Neural Information Processing Systems (NIPS 15), 7-12 December 2015 , Montreal, Canada
https://resolver.caltech.edu/CaltechAUTHORS:20190401-123256793
Huang, Furong; Niranjan, U. N. et al. (2015) Online Tensor Methods for Learning Latent Variable Models Journal of Machine Learning Research; Vol. 16;
https://resolver.caltech.edu/CaltechAUTHORS:20170927-111140656
Anandkumar, Animashree; Hsu, Daniel et al. (2015) When Are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity Journal of Machine Learning Research; Vol. 16;
https://resolver.caltech.edu/CaltechAUTHORS:20170927-144026647
Arabshahi, Forough; Huang, Furong et al. (2015) Are You Going to the Party: Depends, Who Else is Coming?: [Learning Hidden Group Dynamics via Conditional Latent Tree Models] 2015 IEEE International Conference on Data Mining; 2015 IEEE International Conference on Data Mining (ICDM), 14-17 November 2015 , Atlantic City, NJ
https://resolver.caltech.edu/CaltechAUTHORS:20170927-083449769
Anandkumar, Animashree; Ge, Rong et al. (2015) Tensor Decompositions for Learning Latent Variable Models (A Survey for ALT) Algorithmic Learning Theory; Series.Lecture Notes in Computer Science; No. 9355; 26th International Conference on Algorithmic Learning Theory (ALT 2015), October 4-6, 2015 , Banff, Canada
https://resolver.caltech.edu/CaltechAUTHORS:20170920-143816175
Anandkumar, Animashree; Jain, Prateek et al. (2015) Tensor vs Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20190401-123303824
Janzamin, Majid; Sedghi, Hanie et al. (2015) Beating the Perils of Non-Convexity: Guaranteed Training of Neural Networks using Tensor Methods arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20190401-123300368
Huang, Furong; Anandkumar, Animashree (2015) Convolutional Dictionary Learning through Tensor Factorization arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20190401-123253238
Nimmagadda, Tejaswi; Anandkumar, Anima (2015) Multi-Object Classification and Unsupervised Scene Understanding Using Deep Learning Features and Latent Tree Probabilistic Models arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20190401-162932108
Anandkumar, Animashree; Foster, Dean P. et al. (2015) A Spectral Algorithm for Latent Dirichlet Allocation Algorithmica; Vol. 72; No. 1;
https://resolver.caltech.edu/CaltechAUTHORS:20170920-142816744
Janzamin, Majid; Sedghi, Hanie et al. (2015) Score Function Features for Discriminative Learning arXiv; 3rd International Conference on Learning Representations (ICLR 2015), 7-9 May 2015 , San Diego, CA
https://resolver.caltech.edu/CaltechAUTHORS:20190401-162925219
Anandkumar, Anima; Sedghi, Hanie (2015) Learning Mixed Membership Community Models in Social Tagging Networks through Tensor Methods arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20190401-162928669
Sedghi, Hanie; Anandkumar, Anima (2014) Provable Methods for Training Neural Networks with Sparse Connectivity arXiv; Deep Learning and Representation Learning Workshop: NIPS 2014, 12 December 2014 , Montreal, Canada
https://resolver.caltech.edu/CaltechAUTHORS:20190402-163306528
Sedghi, Hanie; Janzamin, Majid et al. (2014) Provable Tensor Methods for Learning Mixtures of Generalized Linear Models Proceedings of Machine Learning Research; Vol. 51; 19th International Conference on Artificial Intelligence and Statistics, 9-11 May 2016 , Cadiz, Spain
https://resolver.caltech.edu/CaltechAUTHORS:20190401-162921773
Janzamin, Majid; Sedghi, Hanie et al. (2014) Score Function Features for Discriminative Learning: Matrix and Tensor Framework arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20190401-162918161
Sedghi, Hanie; Anandkumar, Anima (2014) Provable Methods for Training Neural Networks with Sparse Connectivity arXiv; 3rd International Conference on Learning Representations (ICLR 2015), 7-9 May 2015 , San Diego, CA
https://resolver.caltech.edu/CaltechAUTHORS:20190401-162914714
Sedghi, Hanie; Anandkumar, Anima et al. (2014) Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Matrix Decomposition Advances in neural information processing systems 27 : 28th Annual Conference on Neural Information Processing Systems 2014; 28th Annual Conference on Neural Information Processing Systems (NIPS 2014), 8-13 December 2014 , Montréal, QB
https://resolver.caltech.edu/CaltechAUTHORS:20221222-215036029
Netrapalli, Praneeth; Niranjan, U N et al. (2014) Provable Non-convex Robust PCA Advances in neural information processing systems 27 : 28th Annual Conference on Neural Information Processing Systems 2014; 28th Annual Conference on Neural Information Processing (NIPS 2014), 8-13 December 2014 , Montréal, QB
https://resolver.caltech.edu/CaltechAUTHORS:20221222-220846768
Netrapalli, Praneeth; Niranjan, U N et al. (2014) Non-convex Robust PCA arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20221222-220922210
Anandkumar, Animashree; Ge, Rong et al. (2014) Tensor Decompositions for Learning Latent Variable Models Journal of Machine Learning Research; Vol. 15;
https://resolver.caltech.edu/CaltechAUTHORS:20170927-134735763
Anandkumar, Animashree; Ge, Rong et al. (2014) A Tensor Approach to Learning Mixed Membership Community Models Journal of Machine Learning Research; Vol. 15;
https://resolver.caltech.edu/CaltechAUTHORS:20170927-093022023
Sattari, Pegah; Kurant, Maciej et al. (2014) Active Learning of Multiple Source Multiple Destination Topologies IEEE Transactions on Signal Processing; Vol. 62; No. 8;
https://resolver.caltech.edu/CaltechAUTHORS:20170925-101553300
Janzamin, Majid; Anandkumar, Animashree (2014) High-Dimensional Covariance Decomposition into Sparse Markov and Independence Models Journal of Machine Learning Research; Vol. 15;
https://resolver.caltech.edu/CaltechAUTHORS:20170927-142820777
Sedghi, Hanie; Anandkumar, Anima et al. (2014) Multi-Step Stochastic ADMM in High Dimensions: Applications to Sparse Optimization and Noisy Matrix Decomposition arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20221222-215104749
Anandkumar, Animashree; He, Ting et al. (2013) Seeing through black boxes: Tracking transactions through queues under monitoring resource constraints Performance Evaluation; Vol. 70; No. 12;
https://resolver.caltech.edu/CaltechAUTHORS:20170920-142253537
Anandkumar, Animashree; Hassidim, Avinatan et al. (2013) Topology discovery of sparse random graphs with few participants Random Structures & Algorithms; Vol. 43; No. 1;
https://resolver.caltech.edu/CaltechAUTHORS:20170920-132342501
Anandkumar, Amod J. G.; Anandkumar, Animashree et al. (2013) Robust noncooperative rate-maximization game for MIMO Gaussian interference channels under bounded channel uncertainty 2013 IEEE International Conference on Acoustics, Speech and Signal Processing; 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 26-31 May 2013 , Vancouver, BC
https://resolver.caltech.edu/CaltechAUTHORS:20170925-100945197
Huang, Furong; Anandkumar, Animashree (2013) FCD: Fast-concurrent-distributed load balancing under switching costs and imperfect observations 2013 Proceedings IEEE INFOCOM; 2013 Proceedings IEEE INFOCOM, 14-19 April 2013 , Turin, Italy
https://resolver.caltech.edu/CaltechAUTHORS:20170925-100358224
Sattari, Pegah; Kurant, Maciej et al. (2013) Active learning of multiple source multiple destination topologies 47th Annual Conference on Information Sciences and Systems; 47th Annual Conference on Information Sciences and Systems (CISS), 20-22 March 2013 , Baltimore, MD
https://resolver.caltech.edu/CaltechAUTHORS:20170925-095252031
Anandkumar, Animashree; Valluvan, Ragupathyraj (2013) Learning loopy graphical models with latent variables: Efficient methods and guarantees Annals of Statistics; Vol. 41; No. 2;
https://resolver.caltech.edu/CaltechAUTHORS:20170927-104250746
Anandkumar, Anima; Foster, Dean P. et al. (2012) A Spectral Algorithm for Latent Dirichlet Allocation Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012, NIPS 2012; 26th Annual Conference on Neural Information Processing Systems (NIPS 2012), 3-8 December 2012 , Lake Tahoe, NV
https://resolver.caltech.edu/CaltechAUTHORS:20221222-213700256
Anandkumar, Anima; Valluvan, Ragupathyraj (2012) Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012, NIPS 2012; 26th Annual Conference on Neural Information Processing Systems (NIPS 2012), 3-6 December 2012 , Lake Tahoe, NV
https://resolver.caltech.edu/CaltechAUTHORS:20221222-212818169
Liu, Ying; Chandrasekaran, Venkat et al. (2012) Feedback Message Passing for Inference in Gaussian Graphical Models IEEE Transactions on Signal Processing; Vol. 60; No. 8;
https://resolver.caltech.edu/CaltechAUTHORS:20120820-094221711
Anandkumar, Animashree; Tan, Vincent Y. F. et al. (2012) High-Dimensional Gaussian Graphical Model Selection: Walk Summability and Local Separation Criterion Journal of Machine Learning Research; Vol. 13;
https://resolver.caltech.edu/CaltechAUTHORS:20170927-091743601
Anandkumar, Animashree; Tan, Vincent Y. F. et al. (2012) High-dimensional structure estimation in Ising models: Local separation criterion Annals of Statistics; Vol. 40; No. 3;
https://resolver.caltech.edu/CaltechAUTHORS:20170927-101515951
Anandkumar, Anima; Tan, Voncent Y. F. et al. (2011) High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions Advances in neural information processing systems 24 : 25th Annual Conference on Neural Information Processing Systems 2011, December 12-15, 2011, Granada, Spain; 25th Annual Conference on Neural Information Processing Systems (NIPS 2011), 12-15 December 2011 , Granada, Spain
https://resolver.caltech.edu/CaltechAUTHORS:20221222-193410312
Anandkumar, Animashree; Hsu, Daniel et al. (2011) Learning Mixtures of Tree Graphical Models Advances in neural information processing systems 24 : 25th Annual Conference on Neural Information Processing Systems 2011; 25th Annual Conference on Neural Information Processing Systems (NIPS 2011), 12-17 December 2011 , Granada, Spain
https://resolver.caltech.edu/CaltechAUTHORS:20221222-212034677
Anandkumar, Animashree; Chaudhuri, Kamalika et al. (2011) Spectral Methods for Learning Multivariate Latent Tree Structure Advances in neural information processing systems 24 : 25th Annual Conference on Neural Information Processing Systems 2011, December 12-15, 2011, Granada, Spain; 25th Annual Conference on Neural Information Processing Systems (NIPS 2011), 12-17 December 2011 , Granada, Spain
https://resolver.caltech.edu/CaltechAUTHORS:20221222-190922619
Anandkumar, Amod J. G.; Anandkumar, Animashree et al. (2011) Robust Rate Maximization Game Under Bounded Channel Uncertainty IEEE Transactions on Vehicular Technology; Vol. 60; No. 9; 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, 14-19 March 2010 , Dallas, TX
https://resolver.caltech.edu/CaltechAUTHORS:20170925-094601829
Anandkumar, Animashree; Chaudhuri, Kamalika et al. (2011) Spectral Methods for Learning Multivariate Latent Tree Structure arXiv;
https://resolver.caltech.edu/CaltechAUTHORS:20221222-191039686
Khajehnejad, M. Amin; Yoo, Juhwan et al. (2011) Summary Based Structures with Improved Sublinear Recovery for Compressed Sensing 2011 IEEE International Symposium on Information Theory Proceedings; 2011 IEEE International Symposium on Information Theory (ISIT), Jul 31-Aug 05, 2011 , St. Petersburg, Russia
https://resolver.caltech.edu/CaltechAUTHORS:20120406-072754339
Tan, Vincent Y. F.; Anandkumar, Animashree et al. (2011) Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates Journal of Machine Learning Research; Vol. 12;
https://resolver.caltech.edu/CaltechAUTHORS:20170927-144736867
Choi, Myung Jin; Tan, Vincent Y. F. et al. (2011) Learning Latent Tree Graphical Models Journal of Machine Learning Research; Vol. 12;
https://resolver.caltech.edu/CaltechAUTHORS:20170927-100701408
Anandkumar, Animashree; Michael, Nithin et al. (2011) Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret IEEE Journal on Selected Areas in Communications; Vol. 29; No. 4; 2010 IEEE INFOCOM, 15-19 March 2010 , San Diego, CA
https://resolver.caltech.edu/CaltechAUTHORS:20170922-133040888
Balister, Paul; Bollobás, Béla et al. (2011) Energy-latency tradeoff for in-network function computation in random networks 2011 Proceedings IEEE INFOCOM; 2011 Proceedings IEEE INFOCOM, 10-15 April 2011 , Shanghai, China
https://resolver.caltech.edu/CaltechAUTHORS:20170925-092119382
He, Ting; Anandkumar, Animashree et al. (2011) Index-based sampling policies for tracking dynamic networks under sampling constraints 2011 Proceedings IEEE INFOCOM; 2011 Proceedings IEEE INFOCOM, 10-15 April 2011 , Shanghai, China
https://resolver.caltech.edu/CaltechAUTHORS:20170925-091212425
Tan, Vincent Y. F.; Anandkumar, Animashree et al. (2011) A Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov Tree Structures IEEE Transactions on Information Theory; Vol. 57; No. 3; 2009 International Symposium on Information Theory (ISIT), 28 June - 3 July 2009 , Seoul, Korea
https://resolver.caltech.edu/CaltechAUTHORS:20170922-092634649
Anandkumar, Amod J. G.; Anandkumar, Animashree et al. (2010) Efficiency of rate-maximization game under bounded channel uncertainty 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers; Forty Fourth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2010, 7-10 November 2010 , Pacific Grove, CA
https://resolver.caltech.edu/CaltechAUTHORS:20170922-134024046
Tan, Vincent Y. F.; Anandkumar, Animashree et al. (2010) Error exponents for composite hypothesis testing of Markov forest distributions 2010 IEEE International Symposium on Information Theory; 2010 IEEE International Symposium on Information Theory (ISIT 2010), 13-18 June 2010 , Austin, TX
https://resolver.caltech.edu/CaltechAUTHORS:20170922-085233225
Liu, Ying; Chandrasekaran, Venkat et al. (2010) Feedback Message Passing for Inference in Gaussian Graphical Models 2010 IEEE International Symposium on Information Theory Proceedings (ISIT) ; 2010 IEEE International Symposium on Information Theory (ISIT 2010), 13-18 June 2010 , Austin, TX
https://resolver.caltech.edu/CaltechAUTHORS:20121004-153356182
Anandkumar, Animashree; Yukich, Joseph et al. (2010) Limit laws for random spatial graphical models 2010 IEEE International Symposium on Information Theory; 2010 IEEE International Symposium on Information Theory (ISIT 2010), 13-18 June 2010 , Austin, TX
https://resolver.caltech.edu/CaltechAUTHORS:20170922-084526901
Tan, Vincent Y. F.; Anandkumar, Animashree et al. (2010) Learning Gaussian Tree Models: Analysis of Error Exponents and Extremal Structures IEEE Transactions on Signal Processing; Vol. 58; No. 5; 47th Annual Allerton Conference on Communication, Control, and Computing, 2009. Allerton 2009, September 30 - October 2, 2009 , Monticello, IL
https://resolver.caltech.edu/CaltechAUTHORS:20170922-082655078
Anandkumar, Animashree; Michael, Nithin et al. (2010) Opportunistic Spectrum Access with Multiple Users: Learning under Competition 2010 Proceedings IEEE INFOCOM; 2010 IEEE INFOCOM, 15-19 March 2010 , San Diego, CA
https://resolver.caltech.edu/CaltechAUTHORS:20170922-083321456
Anandkumar, Amod J. G.; Anandkumar, Animashree et al. (2010) Robust rate-maximization game under bounded channel uncertainty 2010 IEEE International Conference on Acoustics, Speech and Signal Processing; 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 14-19 March 2010 , Dallas, TX
https://resolver.caltech.edu/CaltechAUTHORS:20170922-084018628
Tan, Vincent Y. F.; Anandkumar, Animashree et al. (2009) How do the structure and the parameters of Gaussian tree models affect structure learning? 47th Annual Allerton Conference on Communication, Control, and Computing; 47th Annual Allerton Conference on Communication, Control, and Computing, September 30 - October 2, 2009 , Monticello, IL
https://resolver.caltech.edu/CaltechAUTHORS:20170921-160724769
Anandkumar, Animashree; Yukich, Joseph E. et al. (2009) Energy scaling laws for distributed inference in random fusion networks IEEE Journal on Selected Areas in Communications; Vol. 27; No. 7;
https://resolver.caltech.edu/CaltechAUTHORS:20170921-155701400
Tan, Vincent Y. F.; Anandkumar, Animashree et al. (2009) A large-deviation analysis for the maximum likelihood learning of tree structures 2009 IEEE International Symposium on Information Theory; 2009 IEEE International Symposium on Information Theory, June 28 - July 3, 2009 , Seoul, Korea
https://resolver.caltech.edu/CaltechAUTHORS:20170921-154915776
Anandkumar, Animashree; Tong, Lang et al. (2009) Detection error exponent for spatially dependent samples in random networks 2009 IEEE International Symposium on Information Theory; 2009 IEEE International Symposium on Information Theory, June 28 - July 3, 2009 , Seoul, Korea
https://resolver.caltech.edu/CaltechAUTHORS:20170921-154140237
Anandkumar, Animashree; Wang, Meng et al. (2009) Prize-Collecting Data Fusion for Cost-Performance Tradeoff in Distributed Inference 28th IEEE Conference on Computer Communications; 28th IEEE Conference on Computer Communications (INFOCOM 2009), 19-25 April 2009 , Rio de Janeiro, Brazil
https://resolver.caltech.edu/CaltechAUTHORS:20170921-153522501
Anandkumar, Animashree; Tong, Lang et al. (2009) Detection of Gauss-Markov Random Fields With Nearest-Neighbor Dependency IEEE Transactions on Information Theory; Vol. 55; No. 2; 2007 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '07), 15-20 April 2007 , Honolulu, HI
https://resolver.caltech.edu/CaltechAUTHORS:20170920-162015185
Anandkumar, Animashree; Tong, Lang et al. (2008) Optimal Node Density for Detection in Energy-Constrained Random Networks IEEE Transactions on Signal Processing; Vol. 56; No. 10; 45th Allerton Conference on Communication, Control and Computing, 26-28 September 2007 , Monticello, IL
https://resolver.caltech.edu/CaltechAUTHORS:20170920-160524319
Ezovski, G. Matthew; Anandkumar, Animashree et al. (2008) Min-min times in peer-to-peer file sharing networks 46th Annual Allerton Conference on Communication, Control, and Computing; 46th Annual Allerton Conference on Communication, Control, and Computing, 23-26 September 2008 , Urbana-Champaign, IL
https://resolver.caltech.edu/CaltechAUTHORS:20170810-112107197
Anandkumar, Animashree; Tong, Lang et al. (2008) Distributed Estimation Via Random Access IEEE Transactions on Information Theory; Vol. 54; No. 7;
https://resolver.caltech.edu/CaltechAUTHORS:20170920-155855969
Anandkumar, Animashree; Bisdikian, Chatschik et al. (2008) Tracking in a spaghetti bowl: monitoring transactions using footprints Proceedings of the 2008 ACM SIGMETRICS international conference on measurement and modeling of computer systems; 2008 ACM SIGMETRICS international conference on measurement and modeling of computer systems (SIGMETRICS '08), 2-6 June 2008 , Annapolis, MD
https://resolver.caltech.edu/CaltechAUTHORS:20170927-141103230
Anandkumar, Animashree; Tong, Lang et al. (2008) Minimum Cost Data Aggregation with Localized Processing for Statistical Inference 27th IEEE Conference on Computer Communications; 27th IEEE Conference on Computer Communications (INFOCOM 2008), April 15-17, 2008 , Phoenix, AZ
https://resolver.caltech.edu/CaltechAUTHORS:20170920-154142664
Sengupta, Bikram; Banerjee, Nilanjan et al. (2008) Non-intrusive transaction monitoring using system logs 2008 IEEE Network Operations and Management Symposium; 2008 IEEE Network Operations and Management Symposium (NOMS 2008), 7-11 April 2008 , Salvador, Bahia, Brazil
https://resolver.caltech.edu/CaltechAUTHORS:20170920-161153053
Anandkumar, Animashree; Tong, Lang (2007) Type-Based Random Access for Distributed Detection Over Multiaccess Fading Channels IEEE Transactions on Signal Processing; Vol. 55; No. 10;
https://resolver.caltech.edu/CaltechAUTHORS:20170920-153723886
Anandkumar, Animashree; Tong, Lang et al. (2007) Detection of Gauss-Markov Random Field on Nearest-Neighbor Graph 2007 IEEE International Conference on Acoustics, Speech and Signal Processing; 2007 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '07), 15-20 April 2007 , Honolulu, HI
https://resolver.caltech.edu/CaltechAUTHORS:20170920-152542556
Anandkumar, Animashree; Tong, Lang et al. (2007) Energy Efficient Routing for Statistical Inference of Markov Random Fields 2007 41st annual conference on information sciences and systems : Baltimore, MD, 14-16 March, 2007.; 41stConference on Information Sciences and Systems, 14-16 March 2007 , Baltimore, MD
https://resolver.caltech.edu/CaltechAUTHORS:20170920-153229570
Anandkumar, Animashree; Tong, Lang (2006) A Large Deviation Analysis of Detection Over Multi-Access Channels with Random Number of Sensors 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings; Vol. 4; 2006 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), 14-19 May 2006 , Toulouse, France
https://resolver.caltech.edu/CaltechAUTHORS:20170920-144901114
Anandkumar, Animashree; Tong, Lang (2006) Distributed Statistical Inference using Type Based Random Access over Multi-access Fading Channels 2006 40th Annual Conference on Information Sciences and Systems; 2006 40th Annual Conference on Information Sciences and Systems, 22-24 March 2006 , Princeton, NJ
https://resolver.caltech.edu/CaltechAUTHORS:20170920-145744615