Publications (46)
Active Learning of Multiple Source Multiple Destination Topologies
Pegah Sattari, Maciej Kurant, Animashree Anandkumar +2
Learning Latent Tree Graphical Models
Myung Jin Choi, Vincent Y. F. Tan, Animashree Anandkumar +1
Tensor vs Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations
Animashree Anandkumar, Prateek Jain, Yang Shi +1
A Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov Tree Structures
Vincent Y. F. Tan, Animashree Anandkumar, Lang Tong +1
Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
A Clustering Approach to Learn Sparsely-Used Overcomplete Dictionaries
Alekh Agarwal, Animashree Anandkumar, Praneeth Netrapalli
Are you going to the party: depends, who else is coming? [Learning hidden group dynamics via conditional latent tree models]
Forough Arabshahi, Furong Huang, Animashree Anandkumar +2
Nonparametric Estimation of Multi-View Latent Variable Models
Le Song, Animashree Anandkumar, Bo Dai +1
Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies
Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
High-Dimensional Gaussian Graphical Model Selection: Walk Summability and Local Separation Criterion
Animashree Anandkumar, Vincent Y. F. Tan, Alan. S. Willsky
Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret
Animashree Anandkumar, Nithin Michael, Ao Kevin Tang +1
Feedback Message Passing for Inference in Gaussian Graphical Models
Ying Liu, Venkat Chandrasekaran, Animashree Anandkumar +1
Unsupervised Learning of Word-Sequence Representations from Scratch via Convolutional Tensor Decomposition
Furong Huang, Animashree Anandkumar
High Dimensional Structure Learning of Ising Models on Sparse Random Graphs
Animashree Anandkumar, Vincent Tan, Alan Willsky
A Method of Moments for Mixture Models and Hidden Markov Models
Animashree Anandkumar, Daniel Hsu, Sham M. Kakade
Online Tensor Methods for Learning Latent Variable Models
Furong Huang, U. N. Niranjan, Mohammad Umar Hakeem +1
Learning loopy graphical models with latent variables: Efficient methods and guarantees
Animashree Anandkumar, Ragupathyraj Valluvan
Question Type Guided Attention in Visual Question Answering
Yang Shi, Tommaso Furlanello, Sheng Zha +1
Deep Active Learning for Named Entity Recognition
Yanyao Shen, Hyokun Yun, Zachary C. Lipton +2
Learning Gaussian Tree Models: Analysis of Error Exponents and Extremal Structures
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
Reinforcement Learning in Rich-Observation MDPs using Spectral Methods
Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
Tensor Contractions with Extended BLAS Kernels on CPU and GPU
Yang Shi, U. N. Niranjan, Animashree Anandkumar +1
Non-convex Robust PCA
Praneeth Netrapalli, U N Niranjan, Sujay Sanghavi +2
Seeing Through Black Boxes : Tracking Transactions through Queues under Monitoring Resource Constraints
Animashree Anandkumar, Ting He, Chatschik Bisdikian +1
High-Dimensional Covariance Decomposition into Sparse Markov and Independence Models
Majid Janzamin, Animashree Anandkumar
A Spectral Algorithm for Latent Dirichlet Allocation
Animashree Anandkumar, Dean P. Foster, Daniel Hsu +2
Robust Rate-Maximization Game Under Bounded Channel Uncertainty
Amod J. G. Anandkumar, Animashree Anandkumar, Sangarapillai Lambotharan +1
Convolutional Dictionary Learning through Tensor Factorization
Furong Huang, Animashree Anandkumar
Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization
Alekh Agarwal, Animashree Anandkumar, Prateek Jain +1
High-Dimensional Covariance Decomposition into Sparse Markov and Independence Domains
Majid Janzamin, Animashree Anandkumar
Combining Symbolic Expressions and Black-box Function Evaluations in Neural Programs
Forough Arabshahi, Sameer Singh, Animashree Anandkumar
Unsupervised learning of transcriptional regulatory networks via latent tree graphical models
Anthony Gitter, Furong Huang, Ragupathyraj Valluvan +2
High-dimensional structure estimation in Ising models: Local separation criterion
Animashree Anandkumar, Vincent Y. F. Tan, Furong Huang +1
Topology Discovery of Sparse Random Graphs With Few Participants
Animashree Anandkumar, Avinatan Hassidim, Jonathan Kelner
Summary Based Structures with Improved Sublinear Recovery for Compressed Sensing
M. Amin Khajehnejad, Juhwan Yoo, Animashree Anandkumar +1
Fast and Guaranteed Tensor Decomposition via Sketching
Yining Wang, Hsiao-Yu Tung, Alexander Smola +1
Experimental results : Reinforcement Learning of POMDPs using Spectral Methods
Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
Energy-Latency Tradeoff for In-Network Function Computation in Random Networks
Paul Balister, Béla Bollobás, Animashree Anandkumar +1
Sample Complexity Analysis for Learning Overcomplete Latent Variable Models through Tensor Methods
Animashree Anandkumar, Rong Ge, Majid Janzamin
Learning Topic Models and Latent Bayesian Networks Under Expansion Constraints
Animashree Anandkumar, Daniel Hsu, Adel Javanmard +1
Discovering Neuronal Cell Types and Their Gene Expression Profiles Using a Spatial Point Process Mixture Model
Furong Huang, Animashree Anandkumar, Christian Borgs +6
Spectral Methods for Learning Multivariate Latent Tree Structure
Animashree Anandkumar, Kamalika Chaudhuri, Daniel Hsu +3
Spectral Methods for Correlated Topic Models
Forough Arabshahi, Animashree Anandkumar
Detection of Gauss-Markov Random Fields with Nearest-Neighbor Dependency
Animashree Anandkumar, Lang Tong, Ananthram Swami
Energy Scaling Laws for Distributed Inference in Random Fusion Networks
Animashree Anandkumar, Joseph E. Yukich, Lang Tong +1
Online and Differentially-Private Tensor Decomposition
Yining Wang, Animashree Anandkumar