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ISBN 9781713845393; Advances in Neural Information Processing Systems 34
(NeurIPS 2021); Advances in Neural Information Processing Systems;
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Shi, Guanya; Zhu, Yifeng; et el. (2021) Fast
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978-1-7281-9077-8; 2021 IEEE International Conference on Robotics and
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Lale, Sahin; Azizzadenesheli, Kamyar; et el. (2021) Adaptive
Control and Regret Minimization in Linear Quadratic Gaussian (LQG)
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Baldini, Francesca; Anandkumar, Animashree; et el. (2020) Learning
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(DCC); IEEE: Piscataway, NJ; 394; 10.1109/DCC47342.2020.00045
Lale, Sahin; Azizzadenesheli, Kamyar; et el. (2020) Regret
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Arabshahi, Forough; Lu, Zhichu; et el. (2020) Memory
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Jain, Shobhit; Bodapati, Sravan Babu; et el. (2020) Multi
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Schäfer, Florian and Anandkumar, Anima (2019) Competitive
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Cvitkovic, Milan; Singh, Badal; et el. (2019) Open
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Nimmagadda, Tejaswi and Anandkumar, Anima (2019) Multi-Object
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Janzamin, Majid; Sedghi, Hanie; et el. (2019) Score
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Huang, Furong and Anandkumar, Animashree (2019) Convolutional
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Anandkumar, Anima and Ge, Rong (2019) Efficient
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Sedghi, Hanie and Anandkumar, Anima (2019) Training
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Gitter, Anthony; Huang, Furong; et el. (2019) Unsupervised
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ISBN 9781510838819; 30th Annual Conference on Neural Information
Processing Systems 2016 : Barcelona, Spain, 5-10 December 2016; 10.48550/arXiv.1705.02553
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Azizzadenesheli, Kamyar; Liu, Anqi; et el. (2019) Regularized
Learning for Domain Adaptation under Label Shifts ; 10.48550/arXiv.1903.09734
Azizzadenesheli, Kamyar; Lazaric, Alessandro; et el. (2019) Reinforcement
Learning in Rich-Observation MDPs using Spectral Methods ; 10.48550/arXiv.1611.03907v4
Lale, Sahin; Azizzadenesheli, Kamyar; et el. (2019) Stochastic
Linear Bandits with Hidden Low Rank Structure ; 10.48550/arXiv.1901.09490
Kolbeinsson, Arinbjörn; Kossaifi, Jean; et el. (2019) Stochastically
Rank-Regularized Tensor Regression Networks ; 10.48550/arXiv.1902.10758
Azizzadenesheli, Kamyar; Bera, Manish Kumar; et el. (2019) Trust
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Bernstein, Jeremy; Zhao, Jiawei; et el. (2019) signSGD
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Kossaifi, Jean; Panagakis, Yannis; et el. (2019) TensorLy:
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Proceedings of the 56th Annual Meeting of the Association for
Computational Linguistics (Volume 1: Long Papers); Association for
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Khetan, Ashish; Lipton, Zachary C.; et el. (2018) Learning
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Dhillon, Guneet S.; Azizzadenesheli, Kamyar; et el. (2018) Stochastic
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Shi, Yang; Furlanello, Tommaso; et el. (2018) Question
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978-3-030-01224-3; Computer Vision – ECCV 2018; Springer Nature: Cham,
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2018 Information Theory and Applications Workshop (ITA); IEEE:
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Anandkumar, Anima; Deng, Yuan; et el. (2017) Homotopy
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Vol. 65; 79-104; 10.48550/arXiv.1610.09322
Kossaifi, Jean; Khanna, Aran; et el. (2017) Tensor
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978-1-5386-0733-6; 2017 IEEE Conference on Computer Vision and Pattern
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Neural Information Processing Systems 2016; Neural Information
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978-1-5090-5411-4; 2016 IEEE 23rd International Conference on High
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Azizzadenesheli, Kamyar; Lazaric, Alessandro; et el. (2016) Reinforcement
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Wang, Yining; Tung, Hsiao-Yu; et el. (2015) Fast
and Guaranteed Tensor Decomposition via Sketching ; 10.48550/arXiv.1506.04448
Huang, Furong; Niranjan, U. N.; et el. (2015) Online
Tensor Methods for Learning Latent Variable Models ; Journal of
Machine Learning Research; Vol. 16; 2797-2835; 10.48550/arXiv.1309.0787
Anandkumar, Animashree; Hsu, Daniel; et el. (2015) When
Are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker
Decompositions with Structured Sparsity ; Journal of Machine Learning
Research; Vol. 16; 2643-2694; 10.48550/arXiv.1308.2853
Arabshahi, Forough; Huang, Furong; et el. (2015) Are
You Going to the Party: Depends, Who Else is Coming?: [Learning Hidden
Group Dynamics via Conditional Latent Tree Models] ; ISBN
978-1-4673-9504-5; 2015 IEEE International Conference on Data Mining;
IEEE: Piscataway, NJ; 697-702; 10.1109/ICDM.2015.146
Anandkumar, Animashree; Ge, Rong; et el. (2015) Tensor
Decompositions for Learning Latent Variable Models (A Survey for
ALT) ; ISBN 978-3-319-24485-3; Algorithmic Learning Theory; Springer:
Cham, Switzerland; 19-38; 10.1007/978-3-319-24486-0_2
Anandkumar, Animashree; Foster, Dean P.; et el. (2015) A
Spectral Algorithm for Latent Dirichlet Allocation ; Algorithmica;
Vol. 72; No. 1; 193-214; 10.1007/s00453-014-9909-1
Janzamin, Majid; Sedghi, Hanie; et el. (2015) Score
Function Features for Discriminative Learning ; 10.48550/arXiv.1412.6514
Sedghi, Hanie and Anandkumar, Anima (2014) Provable
Methods for Training Neural Networks with Sparse Connectivity ; 10.48550/arXiv.1412.2693
Sedghi, Hanie; Janzamin, Majid; et el. (2014) Provable
Tensor Methods for Learning Mixtures of Generalized Linear Models ;
Proceedings of Machine Learning Research; Vol. 51; 1223-1231; 10.48550/arXiv.1412.3046
Sedghi, Hanie and Anandkumar, Anima (2014) Provable
Methods for Training Neural Networks with Sparse Connectivity ; 10.48550/arXiv.1412.2693
Sedghi, Hanie; Anandkumar, Anima; et el. (2014) Multi-Step
Stochastic ADMM in High Dimensions: Applications to Sparse Optimization
and Matrix Decomposition ; ISBN 9781510800410; Advances in neural
information processing systems 27 : 28th Annual Conference on Neural
Information Processing Systems 2014; Neural Information Processing
Foundation: La Jolla, CA; 1-9
Netrapalli, Praneeth; Niranjan, U N; et el. (2014) Provable
Non-convex Robust PCA ; ISBN 9781510800410; Advances in neural
information processing systems 27 : 28th Annual Conference on Neural
Information Processing Systems 2014; Neural Information Processing
Foundation: La Jolla, CA; 1-9
Anandkumar, Animashree; Ge, Rong; et el. (2014) Tensor
Decompositions for Learning Latent Variable Models ; Journal of
Machine Learning Research; Vol. 15; 2773-2832; 10.48550/arXiv.1210.7559
Anandkumar, Animashree; Ge, Rong; et el. (2014) A
Tensor Approach to Learning Mixed Membership Community Models ;
Journal of Machine Learning Research; Vol. 15; 2239-2312; 10.48550/arXiv.1302.2684
Sattari, Pegah; Kurant, Maciej; et el. (2014) Active
Learning of Multiple Source Multiple Destination Topologies ; IEEE
Transactions on Signal Processing; Vol. 62; No. 8; 1926-1937; 10.1109/TSP.2014.2304431
Janzamin, Majid and Anandkumar, Animashree (2014) High-Dimensional
Covariance Decomposition into Sparse Markov and Independence Models ;
Journal of Machine Learning Research; Vol. 15; 1549-1591; 10.48550/arXiv.1211.0919
Anandkumar, Animashree; He, Ting; et el. (2013) Seeing
through black boxes: Tracking transactions through queues under
monitoring resource constraints ; Performance Evaluation; Vol. 70;
No. 12; 1090-1110; 10.1016/j.peva.2013.08.003
Anandkumar, Animashree; Hassidim, Avinatan; et el. (2013) Topology
discovery of sparse random graphs with few participants ; Random
Structures & Algorithms; Vol. 43; No. 1; 16-48; 10.1002/rsa.20420
Anandkumar, Amod J. G.; Anandkumar, Animashree; et el. (2013) Robust
noncooperative rate-maximization game for MIMO Gaussian interference
channels under bounded channel uncertainty ; ISBN 978-1-4799-0356-6;
2013 IEEE International Conference on Acoustics, Speech and Signal
Processing; IEEE: Piscataway, NJ; 4819-4823; 10.1109/ICASSP.2013.6638576
Huang, Furong and Anandkumar, Animashree (2013) FCD:
Fast-concurrent-distributed load balancing under switching costs and
imperfect observations ; ISBN 978-1-4673-5944-3; 2013 Proceedings
IEEE INFOCOM; IEEE: Piscataway, NJ; 1896-1904; 10.1109/INFCOM.2013.6566989
Sattari, Pegah; Kurant, Maciej; et el. (2013) Active
learning of multiple source multiple destination topologies ; ISBN
978-1-4673-5237-6; 47th Annual Conference on Information Sciences and
Systems; IEEE: Piscataway, NJ; 1-6; 10.1109/CISS.2013.6552253
Anandkumar, Animashree and Valluvan, Ragupathyraj (2013) Learning
loopy graphical models with latent variables: Efficient methods and
guarantees ; Annals of Statistics; Vol. 41; No. 2; 401-435; 10.48550/arXiv.1203.3887
Anandkumar, Anima; Foster, Dean P.; et el. (2012) A
Spectral Algorithm for Latent Dirichlet Allocation
Anandkumar, Anima and Valluvan, Ragupathyraj (2012) Latent
Graphical Model Selection: Efficient Methods for Locally Tree-like
Graphs ; ISBN 9781627480031; Advances in Neural Information
Processing Systems 25: 26th Annual Conference on Neural Information
Processing Systems 2012, NIPS 2012; Neural Information Processing
Foundation: La Jolla, CA; 1-9
Liu, Ying; Chandrasekaran, Venkat; et el. (2012) Feedback
Message Passing for Inference in Gaussian Graphical Models ; IEEE
Transactions on Signal Processing; Vol. 60; No. 8; 4135-4150; 10.1109/TSP.2012.2195656
Anandkumar, Animashree; Tan, Vincent Y. F.; et el. (2012) High-Dimensional
Gaussian Graphical Model Selection: Walk Summability and Local
Separation Criterion ; Journal of Machine Learning Research; Vol. 13;
2293-2337; 10.48550/arXiv.1107.1270
Anandkumar, Animashree; Tan, Vincent Y. F.; et el. (2012) High-dimensional
structure estimation in Ising models: Local separation criterion ;
Annals of Statistics; Vol. 40; No. 3; 1346-1375; 10.48550/arXiv.1107.1736
Anandkumar, Anima; Tan, Voncent Y. F.; et el. (2011) High-Dimensional
Graphical Model Selection: Tractable Graph Families and Necessary
Conditions ; ISBN 9781618395993; Advances in neural information
processing systems 24 : 25th Annual Conference on Neural Information
Processing Systems 2011, December 12-15, 2011, Granada, Spain; Neural
Information Processing Foundation: La Jolla, CA; 1-9
Anandkumar, Animashree; Hsu, Daniel; et el. (2011) Learning
Mixtures of Tree Graphical Models ; ISBN 9781618395993; Advances in
neural information processing systems 24 : 25th Annual Conference on
Neural Information Processing Systems 2011; Neural Information
Processing Foundation: La Jolla, CA; 1-9
Anandkumar, Animashree; Chaudhuri, Kamalika; et el. (2011) Spectral
Methods for Learning Multivariate Latent Tree Structure ; ISBN
9781618395993; Advances in neural information processing systems 24 :
25th Annual Conference on Neural Information Processing Systems 2011,
December 12-15, 2011, Granada, Spain; Neural Information Processing
Foundation: La Jolla, CA; 1-9
Anandkumar, Amod J. G.; Anandkumar, Animashree; et el. (2011) Robust
Rate Maximization Game Under Bounded Channel Uncertainty ; IEEE
Transactions on Vehicular Technology; Vol. 60; No. 9; 4471-4486; 10.1109/TVT.2011.2171011
Anandkumar, Animashree; Chaudhuri, Kamalika; et el. (2011) Spectral
Methods for Learning Multivariate Latent Tree Structure ; 10.48550/arXiv.1107.1283
Khajehnejad, M. Amin; Yoo, Juhwan; et el. (2011) Summary
Based Structures with Improved Sublinear Recovery for Compressed
Sensing ; ISBN 978-1-4577-0596-0; 2011 IEEE International Symposium
on Information Theory Proceedings; IEEE: Piscataway, NJ; 1427-1431; 10.1109/ISIT.2011.6033775
Tan, Vincent Y. F.; Anandkumar, Animashree; et el. (2011) Learning
High-Dimensional Markov Forest Distributions: Analysis of Error
Rates ; Journal of Machine Learning Research; Vol. 12; 1617-1653; 10.48550/arXiv.1005.0766
Choi, Myung Jin; Tan, Vincent Y. F.; et el. (2011) Learning
Latent Tree Graphical Models ; Journal of Machine Learning Research;
Vol. 12; 1771-1812; 10.48550/arXiv.1009.2722
Anandkumar, Animashree; Michael, Nithin; et el. (2011) Distributed
Algorithms for Learning and Cognitive Medium Access with Logarithmic
Regret ; IEEE Journal on Selected Areas in Communications; Vol. 29;
No. 4; 731-745; 10.1109/JSAC.2011.110406
Balister, Paul; Bollobás, Béla; et el. (2011) Energy-latency
tradeoff for in-network function computation in random networks ;
ISBN 978-1-4244-9919-9; 2011 Proceedings IEEE INFOCOM; IEEE: Piscataway,
NJ; 1575-1583; 10.1109/INFCOM.2011.5934949
He, Ting; Anandkumar, Animashree; et el. (2011) Index-based
sampling policies for tracking dynamic networks under sampling
constraints ; ISBN 978-1-4244-9919-9; 2011 Proceedings IEEE INFOCOM;
IEEE: Piscataway, NJ; 1233-1241; 10.1109/INFCOM.2011.5934904
Tan, Vincent Y. F.; Anandkumar, Animashree; et el. (2011) A
Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov
Tree Structures ; IEEE Transactions on Information Theory; Vol. 57;
No. 3; 1714-1735; 10.1109/TIT.2011.2104513
Anandkumar, Amod J. G.; Anandkumar, Animashree; et el. (2010) Efficiency
of rate-maximization game under bounded channel uncertainty ; ISBN
978-1-4244-9722-5; 2010 Conference Record of the Forty Fourth Asilomar
Conference on Signals, Systems and Computers; IEEE: Piscataway, NJ;
482-486; 10.1109/ACSSC.2010.5757605
Tan, Vincent Y. F.; Anandkumar, Animashree; et el. (2010) Error
exponents for composite hypothesis testing of Markov forest
distributions ; ISBN 978-1-4244-7890-3; 2010 IEEE International
Symposium on Information Theory; IEEE: Piscataway, NJ; 1613-1617; 10.1109/ISIT.2010.5513399
Liu, Ying; Chandrasekaran, Venkat; et el. (2010) Feedback
Message Passing for Inference in Gaussian Graphical Models ; ISBN
978-1-4244-6960-4; 2010 IEEE International Symposium on Information
Theory Proceedings (ISIT); IEEE: Piscataway, NJ; 1683-1687; 10.1109/ISIT.2010.5513321
Anandkumar, Animashree; Yukich, Joseph; et el. (2010) Limit
laws for random spatial graphical models ; ISBN 978-1-4244-7890-3;
2010 IEEE International Symposium on Information Theory; IEEE:
Piscataway, NJ; 1728-1732; 10.1109/ISIT.2010.5513254
Tan, Vincent Y. F.; Anandkumar, Animashree; et el. (2010) Learning
Gaussian Tree Models: Analysis of Error Exponents and Extremal
Structures ; IEEE Transactions on Signal Processing; Vol. 58; No. 5;
2701-2714; 10.1109/TSP.2010.2042478
Anandkumar, Animashree; Michael, Nithin; et el. (2010) Opportunistic
Spectrum Access with Multiple Users: Learning under Competition ;
ISBN 978-1-4244-5836-3; 2010 Proceedings IEEE INFOCOM; IEEE: Piscataway,
NJ; 1-9; 10.1109/INFCOM.2010.5462144
Anandkumar, Amod J. G.; Anandkumar, Animashree; et el. (2010) Robust
rate-maximization game under bounded channel uncertainty ; ISBN
978-1-4244-4295-9; 2010 IEEE International Conference on Acoustics,
Speech and Signal Processing; IEEE: Piscataway, NJ; 3158-3161; 10.1109/ICASSP.2010.5496066
Tan, Vincent Y. F.; Anandkumar, Animashree; et el. (2009) How
do the structure and the parameters of Gaussian tree models affect
structure learning? ; ISBN 978-1-4244-5870-7; 47th Annual Allerton
Conference on Communication, Control, and Computing; IEEE: Piscataway,
NJ; 684-691; 10.1109/ALLERTON.2009.5394929
Anandkumar, Animashree; Yukich, Joseph E.; et el. (2009) Energy
scaling laws for distributed inference in random fusion networks ;
IEEE Journal on Selected Areas in Communications; Vol. 27; No. 7;
1203-1217; 10.1109/JSAC.2009.090916
Tan, Vincent Y. F.; Anandkumar, Animashree; et el. (2009) A
large-deviation analysis for the maximum likelihood learning of tree
structures ; ISBN 978-1-4244-4312-3; 2009 IEEE International
Symposium on Information Theory; IEEE: Piscataway, NJ; 1140-1144; 10.1109/ISIT.2009.5206012
Anandkumar, Animashree; Tong, Lang; et el. (2009) Detection
error exponent for spatially dependent samples in random networks ;
ISBN 978-1-4244-4312-3; 2009 IEEE International Symposium on Information
Theory; IEEE: Piscataway, NJ; 2882-2886; 10.1109/ISIT.2009.5205358
Anandkumar, Animashree; Wang, Meng; et el. (2009) Prize-Collecting
Data Fusion for Cost-Performance Tradeoff in Distributed Inference ;
ISBN 978-1-4244-3512-8; 28th IEEE Conference on Computer Communications;
IEEE: Piscataway, NJ; 2150-2158; 10.1109/INFCOM.2009.5062139
Anandkumar, Animashree; Tong, Lang; et el. (2009) Detection
of Gauss-Markov Random Fields With Nearest-Neighbor Dependency ; IEEE
Transactions on Information Theory; Vol. 55; No. 2; 816-827; 10.1109/TIT.2008.2009855
Anandkumar, Animashree; Tong, Lang; et el. (2008) Optimal
Node Density for Detection in Energy-Constrained Random Networks ;
IEEE Transactions on Signal Processing; Vol. 56; No. 10; 5232-5245; 10.1109/TSP.2008.928514
Ezovski, G. Matthew; Anandkumar, Animashree; et el. (2008) Min-min
times in peer-to-peer file sharing networks ; ISBN 978-1-4244-2925-7;
46th Annual Allerton Conference on Communication, Control, and
Computing; IEEE: Piscataway, NJ; 1487-1494; 10.1109/ALLERTON.2008.4797738
Anandkumar, Animashree; Tong, Lang; et el. (2008) Distributed
Estimation Via Random Access ; IEEE Transactions on Information
Theory; Vol. 54; No. 7; 3175-3181; 10.1109/TIT.2008.924652
Anandkumar, Animashree; Bisdikian, Chatschik; et el. (2008) Tracking
in a spaghetti bowl: monitoring transactions using footprints ; ISBN
978-1-60558-005-0; Proceedings of the 2008 ACM SIGMETRICS international
conference on measurement and modeling of computer systems; Association
for Computing Machinery: New York, NY; 133-144; 10.1145/1375457.1375473
Anandkumar, Animashree; Tong, Lang; et el. (2008) Minimum
Cost Data Aggregation with Localized Processing for Statistical
Inference ; ISBN 978-1-4244-2025-4; 27th IEEE Conference on Computer
Communications; IEEE: Piscataway, NJ; 1454-1462; 10.1109/INFOCOM.2008.129
Sengupta, Bikram; Banerjee, Nilanjan; et el. (2008) Non-intrusive
transaction monitoring using system logs ; ISBN 978-1-4244-2065-0;
2008 IEEE Network Operations and Management Symposium; IEEE: Piscataway,
NJ; 879-882; 10.1109/NOMS.2008.4575237
Anandkumar, Animashree and Tong, Lang (2007) Type-Based
Random Access for Distributed Detection Over Multiaccess Fading
Channels ; IEEE Transactions on Signal Processing; Vol. 55; No. 10;
5032-5043; 10.1109/TSP.2007.896302
Anandkumar, Animashree; Tong, Lang; et el. (2007) Detection
of Gauss-Markov Random Field on Nearest-Neighbor Graph ; ISBN
1-4244-0727-3; 2007 IEEE International Conference on Acoustics, Speech
and Signal Processing; IEEE: Piscataway, NJ; 829-832; 10.1109/ICASSP.2007.366808
Anandkumar, Animashree; Tong, Lang; et el. (2007) Energy
Efficient Routing for Statistical Inference of Markov Random Fields ;
ISBN 9781424410361; 2007 41st annual conference on information sciences
and systems : Baltimore, MD, 14-16 March, 2007.; IEEE: Piscataway, NJ;
643-648; 10.1109/CISS.2007.4298386
Anandkumar, Animashree and Tong, Lang (2006) A
Large Deviation Analysis of Detection Over Multi-Access Channels with
Random Number of Sensors ; ISBN 1-4244-0469-X; 2006 IEEE
International Conference on Acoustics Speed and Signal Processing
Proceedings; IEEE: Piscataway, NJ; 1097-1100; 10.1109/ICASSP.2006.1661164
Anandkumar, Animashree and Tong, Lang (2006) Distributed
Statistical Inference using Type Based Random Access over Multi-access
Fading Channels ; ISBN 1-4244-0349-9; 2006 40th Annual Conference on
Information Sciences and Systems; IEEE: Piscataway, NJ; 38-43; 10.1109/CISS.2006.286427
