Animashree Anandkumar

205 papers A* 45A 5B 9C 1Misc 8Journal 115Unranked 22

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Self-Supervised Learning via Flow-Guided Neural Operator on Time-Series Data. CoRR Duy Nguyen, Jiachen Yao, Jiayun Wang, Julius Berner, Animashree Anandkumar
2025	J	`jnl`	Analyzing Political Text at Scale with Online Tensor LDA. CoRR Sara Kangaslahti, Danny Ebanks, Jean Kossaifi, Anqi Liu, R. Michael Alvarez, Animashree Anandkumar
2025	J	`jnl`	Online Moderation in Competitive Action Games: How Intervention Affects Player Behaviors. Proc. ACM Hum. Comput. Interact. Rafal Kocielnik, Zhuofang Li, Mitchell Linegar, Deshawn Sambrano, Fereshteh Soltani, Min Kim, Nabiha Naqvie, Grant Cahill, Animashree Anandkumar, R. Michael Alvarez
2025	J	`jnl`	Prosocial Behavior Detection in Player Game Chat: From Aligning Human-AI Definitions to Efficient Annotation at Scale. CoRR Rafal Kocielnik, Min Kim, Penphob Boonyarungsrit, Fereshteh Soltani, Deshawn Sambrano, Animashree Anandkumar, R. Michael Alvarez
2025	J	`jnl`	Self-Anchored Attention Model for Sample-Efficient Classification of Prosocial Text Chat. CoRR Zhuofang Li, Rafal Kocielnik, Fereshteh Soltani, Penphob Boonyarungsrit, Animashree Anandkumar, R. Michael Alvarez
2024	A*	`conf`	CARE: a Benchmark Suite for the Classification and Retrieval of Enzymes. NeurIPS Jason Yang, Ariane Mora, Shengchao Liu, Bruce J. Wittmann, Animashree Anandkumar, Frances H. Arnold, Yisong Yue
2024	J	`jnl`	Challenges in moderating disruptive player behavior in online competitive action games. Frontiers Comput. Sci. Rafal Kocielnik, Zhuofang Li, Claudia Kann, Deshawn Sambrano, Jacob Morrier, Mitchell Linegar, Carly Taylor, Min Kim, Nabiha Naqvie, Feri Soltani, Arman Dehpanah, Grant Cahill, Animashree Anandkumar, R. Michael Alvarez
2024	A	`conf`	Differentially Private Video Activity Recognition. WACV Zelun Luo, Yuliang Zou, Yijin Yang, Zane Durante, De-An Huang, Zhiding Yu, Chaowei Xiao, Li Fei-Fei, Animashree Anandkumar
2024	A*	`conf`	Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization. NeurIPS Mucong Ding, Chenghao Deng, Jocelyn Choo, Zichu Wu, Aakriti Agrawal, Avi Schwarzschild, Tianyi Zhou, Tom Goldstein, John Langford, Animashree Anandkumar, Furong Huang
2024	A*	`conf`	Mini-Sequence Transformers: Optimizing Intermediate Memory for Long Sequences Training. NeurIPS Cheng Luo, Jiawei Zhao, Zhuoming Chen, Beidi Chen, Animashree Anandkumar
2024	J	`jnl`	Online Moderation in Competitive Action Games: How Intervention Affects Player Behaviors. CoRR Zhuofang Li, Rafal Kocielnik, Mitchell Linegar, Deshawn Sambrano, Fereshteh Soltani, Min Kim, Nabiha Naqvie, Grant Cahill, Animashree Anandkumar, R. Michael Alvarez
2024	A*	`conf`	Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs. NeurIPS Md. Ashiqur Rahman, Robert Joseph George, Mogab Elleithy, Daniel V. Leibovici, Zongyi Li, Boris Bonev, Colin White, Julius Berner, Raymond A. Yeh, Jean Kossaifi, Kamyar Azizzadenesheli, Animashree Anandkumar
2024	J	`jnl`	State-specific protein-ligand complex structure prediction with a multiscale deep generative model. Nat. Mac. Intell. Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Animashree Anandkumar
2023	A*	`conf`	ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard
2023	J	`jnl`	Differentially Private Video Activity Recognition. CoRR Zelun Luo, Yuliang Zou, Yijin Yang, Zane Durante, De-An Huang, Zhiding Yu, Chaowei Xiao, Li Fei-Fei, Animashree Anandkumar
2023	A	`conf`	Distributionally Robust Policy Gradient for Offline Contextual Bandits. AISTATS Zhouhao Yang, Yihong Guo, Pan Xu, Anqi Liu, Animashree Anandkumar
2023	J	`jnl`	FocalFormer3D : Focusing on Hard Instance for 3D Object Detection. CoRR Yilun Chen, Zhiding Yu, Yukang Chen, Shiyi Lan, Animashree Anandkumar, Jiaya Jia, José M. Álvarez
2023	A*	`conf`	Geometry-Informed Neural Operator for Large-Scale 3D PDEs. NeurIPS Zongyi Li, Nikola B. Kovachki, Christopher B. Choy, Boyi Li, Jean Kossaifi, Shourya Prakash Otta, Mohammad Amin Nabian, Maximilian Stadler, Christian Hundt, Kamyar Azizzadenesheli, Animashree Anandkumar
2023	J	`jnl`	Human visual explanations mitigate bias in AI-based assessment of surgeon skills. npj Digit. Medicine Dani Kiyasseh, Jasper Laca, Taseen F. Haque, Maxwell X. Otiato, Brian J. Miles, Christian Wagner, Daniel A. Donoho, Quoc-Dien Trinh, Animashree Anandkumar, Andrew J. Hung
2023	A*	`conf`	LeanDojo: Theorem Proving with Retrieval-Augmented Language Models. NeurIPS Kaiyu Yang, Aidan M. Swope, Alex Gu, Rahul Chalamala, Peiyang Song, Shixing Yu, Saad Godil, Ryan J. Prenger, Animashree Anandkumar
2023	A*	`conf`	Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach. IJCAI Haoxuan Wang, Zhiding Yu, Yisong Yue, Animashree Anandkumar, Anqi Liu, Junchi Yan
2023	J	`jnl`	Multi-modal molecule structure-text model for text-based retrieval and editing. Nat. Mac. Intell. Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang, Chaowei Xiao, Animashree Anandkumar
2023	A*	`conf`	Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials. NeurIPS Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Zhiling Zheng, Chenru Duan, Zhi-Ming Ma, Omar Yaghi, Animashree Anandkumar, Christian Borgs, Jennifer T. Chayes, Hongyu Guo, Jian Tang
2022	A*	`conf`	Diffusion Models for Adversarial Purification. ICML Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Animashree Anandkumar
2022	J	`jnl`	FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators. CoRR Jaideep Pathak, Shashank Subramanian, Peter Harrington, Sanjeev Raja, Ashesh Chattopadhyay, Morteza Mardani, Thorsten Kurth, David Hall, Zongyi Li, Kamyar Azizzadenesheli, Pedram Hassanzadeh, Karthik Kashinath, Animashree Anandkumar
2022	J	`jnl`	FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators. CoRR Thorsten Kurth, Shashank Subramanian, Peter Harrington, Jaideep Pathak, Morteza Mardani, David Hall, Andrea Miele, Karthik Kashinath, Animashree Anandkumar
2022	A*	`conf`	Langevin Monte Carlo for Contextual Bandits. ICML Pan Xu, Hongkai Zheng, Eric V. Mazumdar, Kamyar Azizzadenesheli, Animashree Anandkumar
2022	J	`jnl`	Neural Scene Representation for Locomotion on Structured Terrain. CoRR David Hoeller, Nikita Rudin, Christopher B. Choy, Animashree Anandkumar, Marco Hutter
2022	J	`jnl`	Neural Scene Representation for Locomotion on Structured Terrain. IEEE Robotics Autom. Lett. David Hoeller, Nikita Rudin, Christopher B. Choy, Animashree Anandkumar, Marco Hutter
2022	J	`jnl`	PeRFception: Perception using Radiance Fields. CoRR Yoonwoo Jeong, Seungjoo Shin, Junha Lee, Christopher B. Choy, Animashree Anandkumar, Minsu Cho, Jaesik Park
2022	J	`jnl`	Quantification of Robotic Surgeries with Vision-Based Deep Learning. CoRR Dani Kiyasseh, Runzhuo Ma, Taseen F. Haque, Jessica H. Nguyen, Christian Wagner, Animashree Anandkumar, Andrew J. Hung
2022	A	`conf`	Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems. AISTATS Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Animashree Anandkumar
2022	J	`jnl`	Surgical gestures as a method to quantify surgical performance and predict patient outcomes. npj Digit. Medicine Runzhuo Ma, Ashwin Ramaswamy, Jiashu Xu, Loc Trinh, Dani Kiyasseh, Timothy N. Chu, Elyssa Y. Wong, Ryan S. Lee, Ivan Rodriguez, Gina Demeo, Aditya Desai, Maxwell X. Otiato, Sidney I. Roberts, Jessica H. Nguyen, Jasper Laca, Yan Liu, Katarina Urbanova, Christian Wagner, Animashree Anandkumar, Jim C. Hu, Andrew J. Hung
2022	A*	`conf`	Thompson Sampling Achieves $\tilde{O}(\sqrt{T})$ Regret in Linear Quadratic Control. COLT Taylan Kargin, Sahin Lale, Kamyar Azizzadenesheli, Animashree Anandkumar, Babak Hassibi
2022	A*	`conf`	Understanding The Robustness in Vision Transformers. ICML Daquan Zhou, Zhiding Yu, Enze Xie, Chaowei Xiao, Animashree Anandkumar, Jiashi Feng, José M. Álvarez
2021	A	`conf`	Active Learning under Label Shift. AISTATS Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue
2021	J	`jnl`	Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition. CoRR Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Animashree Anandkumar
2021	A*	`conf`	Deep Bayesian Quadrature Policy Optimization. AAAI Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Animashree Anandkumar, Yisong Yue
2021	A*	`conf`	Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objects. ICRA Xinlei Pan, Animesh Garg, Animashree Anandkumar, Yuke Zhu
2021	A*	`conf`	Fast Uncertainty Quantification for Deep Object Pose Estimation. ICRA Guanya Shi, Yifeng Zhu, Jonathan Tremblay, Stan Birchfield, Fabio Ramos, Animashree Anandkumar, Yuke Zhu
2021	A*	`conf`	Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection. ICML Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Animashree Anandkumar, Sanja Fidler, José M. Álvarez
2021	J	`jnl`	Reinforcement Learning in Factored Action Spaces using Tensor Decompositions. CoRR Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar
2021	—	`conf`	Robust Reinforcement Learning: A Constrained Game-theoretic Approach. L4DC Jing Yu, Clement Gehring, Florian Schäfer, Animashree Anandkumar
2021	A*	`conf`	SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies. ICML Linxi Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Animashree Anandkumar
2021	A*	`conf`	Self-Calibrating Neural Radiance Fields. ICCV Yoonwoo Jeong, Seokjun Ahn, Christopher B. Choy, Animashree Anandkumar, Minsu Cho, Jaesik Park
2021	J	`jnl`	Self-Calibrating Neural Radiance Fields. CoRR Yoonwoo Jeong, Seokjun Ahn, Christopher B. Choy, Animashree Anandkumar, Minsu Cho, Jaesik Park
2021	J	`jnl`	Tensor Dropout for Robust Learning. IEEE J. Sel. Top. Signal Process. Arinbjörn Kolbeinsson, Jean Kossaifi, Yannis Panagakis, Adrian Bulat, Animashree Anandkumar, Ioanna Tzoulaki, Paul M. Matthews
2021	A*	`conf`	Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. ICML Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar
2021	J	`jnl`	Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. CoRR Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar
2020	J	`jnl`	Active Learning under Label Shift. CoRR Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue
2020	A*	`conf`	Angular Visual Hardness. ICML Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Animashree Anandkumar
2020	A*	`conf`	Automated Synthetic-to-Real Generalization. ICML Wuyang Chen, Zhiding Yu, Zhangyang Wang, Animashree Anandkumar
2020	J	`jnl`	Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning. CoRR Weili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Animashree Anandkumar
2020	J	`jnl`	Causal Discovery in Physical Systems from Videos. CoRR Yunzhu Li, Antonio Torralba, Animashree Anandkumar, Dieter Fox, Animesh Garg
2020	J	`jnl`	Convolutional Tensor-Train LSTM for Spatio-temporal Learning. CoRR Jiahao Su, Wonmin Byeon, Furong Huang, Jan Kautz, Animashree Anandkumar
2020	J	`jnl`	Deep learning-based computer vision to recognize and classify suturing gestures in robot-assisted surgery. CoRR Francisco Luongo, Ryan Hakim, Jessica H. Nguyen, Animashree Anandkumar, Andrew J. Hung
2020	J	`jnl`	Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objects. CoRR Xinlei Pan, Animesh Garg, Animashree Anandkumar, Yuke Zhu
2020	J	`jnl`	Fast Uncertainty Quantification for Deep Object Pose Estimation. CoRR Guanya Shi, Yifeng Zhu, Jonathan Tremblay, Stan Birchfield, Fabio Ramos, Animashree Anandkumar, Yuke Zhu
2020	B	`conf`	Higher-Order Count Sketch: Dimensionality Reduction that Retains Efficient Tensor Operations. DCC Yang Shi, Animashree Anandkumar
2020	A*	`conf`	Implicit competitive regularization in GANs. ICML Florian Schäfer, Hongkai Zheng, Animashree Anandkumar
2020	C	`conf`	Learning Pose Estimation for UAV Autonomous Navigation and Landing Using Visual-Inertial Sensor Data. ACC Francesca Baldini, Animashree Anandkumar, Richard M. Murray
2020	J	`jnl`	Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion. CoRR Xingye Da, Zhaoming Xie, David Hoeller, Byron Boots, Animashree Anandkumar, Yuke Zhu, Buck Babich, Animesh Garg
2020	J	`jnl`	Multi-task learning for electronic structure to predict and explore molecular potential energy surfaces. CoRR Zhuoran Qiao, Feizhi Ding, Matthew Welborn, Peter J. Bygrave, Daniel G. A. Smith, Animashree Anandkumar, Frederick R. Manby, Thomas F. Miller III
2020	A	`conf`	OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation. UAI Hongyu Ren, Yuke Zhu, Jure Leskovec, Animashree Anandkumar, Animesh Garg
2020	J	`jnl`	OrbNet: Deep Learning for Quantum Chemistry Using Symmetry-Adapted Atomic-Orbital Features. CoRR Zhuoran Qiao, Matthew Welborn, Animashree Anandkumar, Frederick R. Manby, Thomas F. Miller III
2020	Misc	`conf`	Role of HPC in next-generation AI. HiPC Animashree Anandkumar
2020	A*	`conf`	Semi-Supervised StyleGAN for Disentanglement Learning. ICML Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Animashree Anandkumar
2019	J	`jnl`	Learning Pose Estimation for UAV Autonomous Navigation andLanding Using Visual-Inertial Sensor Data. CoRR Francesca Baldini, Animashree Anandkumar, Richard M. Murray
2019	J	`jnl`	Memory Augmented Recursive Neural Networks. CoRR Forough Arabshahi, Zhichu Lu, Sameer Singh, Animashree Anandkumar
2019	J	`jnl`	Multi-dimensional Tensor Sketch. CoRR Yang Shi, Animashree Anandkumar
2019	A*	`conf`	Neural Lander: Stable Drone Landing Control Using Learned Dynamics. ICRA Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung
2019	A*	`conf`	Open Vocabulary Learning on Source Code with a Graph-Structured Cache. ICML Milan Cvitkovic, Badal Singh, Animashree Anandkumar
2019	—	`conf`	Regularized Learning for Domain Adaptation under Label Shifts. ICLR (Poster) Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar
2019	J	`jnl`	Regularized Learning for Domain Adaptation under Label Shifts. CoRR Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar
2018	—	`conf`	Combining Symbolic Expressions and Black-box Function Evaluations in Neural Programs. ICLR (Poster) Forough Arabshahi, Sameer Singh, Animashree Anandkumar
2018	J	`jnl`	Combining Symbolic and Function Evaluation Expressions In Neural Programs. CoRR Forough Arabshahi, Sameer Singh, Animashree Anandkumar
2018	—	`conf`	Deep Active Learning for Named Entity Recognition. ICLR (Poster) Yanyao Shen, Hyokun Yun, Zachary C. Lipton, Yakov Kronrod, Animashree Anandkumar
2018	Misc	`conf`	Efficient Exploration Through Bayesian Deep Q-Networks. ITA Kamyar Azizzadenesheli, Emma Brunskill, Animashree Anandkumar
2018	J	`jnl`	Efficient Exploration through Bayesian Deep Q-Networks. CoRR Kamyar Azizzadenesheli, Emma Brunskill, Animashree Anandkumar
2018	—	`conf`	Learning From Noisy Singly-labeled Data. ICLR (Poster) Ashish Khetan, Zachary C. Lipton, Animashree Anandkumar
2018	J	`jnl`	Neural Lander: Stable Drone Landing Control using Learned Dynamics. CoRR Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung
2018	—	`conf`	Question Type Guided Attention in Visual Question Answering. ECCV (4) Yang Shi, Tommaso Furlanello, Sheng Zha, Animashree Anandkumar
2018	J	`jnl`	Question Type Guided Attention in Visual Question Answering. CoRR Yang Shi, Tommaso Furlanello, Sheng Zha, Animashree Anandkumar
2018	A*	`conf`	SIGNSGD: Compressed Optimisation for Non-Convex Problems. ICML Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Animashree Anandkumar
2018	J	`jnl`	Sample-Efficient Deep RL with Generative Adversarial Tree Search. CoRR Kamyar Azizzadenesheli, Brandon Yang, Weitang Liu, Emma Brunskill, Zachary C. Lipton, Animashree Anandkumar
2018	—	`conf`	Stochastic Activation Pruning for Robust Adversarial Defense. ICLR (Poster) Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, Animashree Anandkumar
2018	A*	`conf`	StrassenNets: Deep Learning with a Multiplication Budget. ICML Michael Tschannen, Aran Khanna, Animashree Anandkumar
2018	J	`jnl`	Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152). Dagstuhl Manifestos Evrim Acar, Animashree Anandkumar, Lenore Mullin, Sebnem Rusitschka, Volker Tresp
2018	J	`jnl`	Trust Region Policy Optimization of POMDPs. CoRR Kamyar Azizzadenesheli, Manish Kumar Bera, Animashree Anandkumar
2017	J	`jnl`	A Clustering Approach to Learning Sparsely Used Overcomplete Dictionaries. IEEE Trans. Inf. Theory Alekh Agarwal, Animashree Anandkumar, Praneeth Netrapalli
2017	J	`jnl`	Analyzing Tensor Power Method Dynamics in Overcomplete Regime. J. Mach. Learn. Res. Animashree Anandkumar, Rong Ge, Majid Janzamin
2017	—	`conf`	Deep Active Learning for Named Entity Recognition. Rep4NLP@ACL Yanyao Shen, Hyokun Yun, Zachary Chase Lipton, Yakov Kronrod, Animashree Anandkumar
2017	J	`jnl`	Deep Active Learning for Named Entity Recognition. CoRR Yanyao Shen, Hyokun Yun, Zachary C. Lipton, Yakov Kronrod, Animashree Anandkumar
2017	J	`jnl`	Experimental results : Reinforcement Learning of POMDPs using Spectral Methods. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	J	`jnl`	Beyond LDA: A Unified Framework for Learning Latent Normalized Infinitely Divisible Topic Models through Spectral Methods. CoRR Forough Arabshahi, Animashree Anandkumar
2016	A*	`conf`	Efficient approaches for escaping higher order saddle points in non-convex optimization. COLT Animashree Anandkumar, Rong Ge
2016	J	`jnl`	Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization. SIAM J. Optim. Alekh Agarwal, Animashree Anandkumar, Prateek Jain, Praneeth Netrapalli
2016	J	`jnl`	Online and Differentially-Private Tensor Decomposition. CoRR Yining Wang, Animashree Anandkumar
2016	A*	`conf`	Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies. COLT Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	J	`jnl`	Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	J	`jnl`	Reinforcement Learning of Contextual MDPs using Spectral Methods. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	J	`jnl`	Reinforcement Learning of POMDP's using Spectral Methods. CoRR Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	A*	`conf`	Reinforcement Learning of POMDPs using Spectral Methods. COLT Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar
2016	J	`jnl`	Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152). Dagstuhl Reports Evrim Acar, Animashree Anandkumar, Lenore Mullin, Sebnem Rusitschka, Volker Tresp
2016	Misc	`conf`	Tensor Contractions with Extended BLAS Kernels on CPU and GPU. HiPC Yang Shi, U. N. Niranjan, Animashree Anandkumar, Cris Cecka
2016	J	`jnl`	Tensor Contractions with Extended BLAS Kernels on CPU and GPU. CoRR Yang Shi, U. N. Niranjan, Animashree Anandkumar, Cris Cecka
2016	J	`jnl`	Unsupervised learning of transcriptional regulatory networks via latent tree graphical models. CoRR Anthony Gitter, Furong Huang, Ragupathyraj Valluvan, Ernest Fraenkel, Animashree Anandkumar
2015	A*	`conf`	Are You Going to the Party: Depends, Who Else is Coming?: [Learning Hidden Group Dynamics via Conditional Latent Tree Models]. ICDM Forough Arabshahi, Furong Huang, Animashree Anandkumar, Carter T. Butts, Sean M. Fitzhugh
2015	—	`conf`	Convolutional Dictionary Learning through Tensor Factorization. FE@NIPS Furong Huang, Animashree Anandkumar
2015	J	`jnl`	Convolutional Dictionary Learning through Tensor Factorization. CoRR Furong Huang, Animashree Anandkumar
2015	—	`conf`	FEAST at Play: Feature ExtrAction using Score function Tensors. FE@NIPS Majid Janzamin, Hanie Sedghi, U. N. Niranjan, Animashree Anandkumar
2015	J	`jnl`	Fast and Guaranteed Tensor Decomposition via Sketching. CoRR Yining Wang, Hsiao-Yu Fish Tung, Alexander J. Smola, Animashree Anandkumar
2015	A*	`conf`	Learning Overcomplete Latent Variable Models through Tensor Methods. COLT Animashree Anandkumar, Rong Ge, Majid Janzamin
2015	J	`jnl`	Online tensor methods for learning latent variable models. J. Mach. Learn. Res. Furong Huang, U. N. Niranjan, Mohammad Umar Hakeem, Animashree Anandkumar
2015	J	`jnl`	Tensor vs Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations. CoRR Animashree Anandkumar, Prateek Jain, Yang Shi, U. N. Niranjan
2015	J	`jnl`	When are overcomplete topic models identifiable? uniqueness of tensor tucker decompositions with structured sparsity. J. Mach. Learn. Res. Animashree Anandkumar, Daniel J. Hsu, Majid Janzamin, Sham M. Kakade
2014	J	`jnl`	A tensor approach to learning mixed membership community models. J. Mach. Learn. Res. Animashree Anandkumar, Rong Ge, Daniel J. Hsu, Sham M. Kakade
2014	J	`jnl`	Active Learning of Multiple Source Multiple Destination Topologies. IEEE Trans. Signal Process. Pegah Sattari, Maciej Kurant, Animashree Anandkumar, Athina Markopoulou, Michael G. Rabbat
2014	J	`jnl`	Guaranteed Non-Orthogonal Tensor Decomposition via Alternating Rank-1 Updates. CoRR Animashree Anandkumar, Rong Ge, Majid Janzamin
2014	J	`jnl`	High-dimensional covariance decomposition into sparse Markov and independence models. J. Mach. Learn. Res. Majid Janzamin, Animashree Anandkumar
2014	J	`jnl`	Integrated Structure and Parameters Learning in Latent Tree Graphical Models. CoRR Furong Huang, U. N. Niranjan, Animashree Anandkumar
2014	A*	`conf`	Learning Sparsely Used Overcomplete Dictionaries. COLT Alekh Agarwal, Animashree Anandkumar, Prateek Jain, Praneeth Netrapalli, Rashish Tandon
2014	J	`jnl`	Modeling Dynamic Social Interactions via Conditional Latent Tree Models. CoRR Forough Arabshahi, Furong Huang, Animashree Anandkumar, Carter T. Butts
2014	—	`conf`	Non-convex Robust PCA. NIPS Praneeth Netrapalli, U. N. Niranjan, Sujay Sanghavi, Animashree Anandkumar, Prateek Jain
2014	J	`jnl`	Non-convex Robust PCA. CoRR Praneeth Netrapalli, U. N. Niranjan, Sujay Sanghavi, Animashree Anandkumar, Prateek Jain
2014	A*	`conf`	Nonparametric Estimation of Multi-View Latent Variable Models. ICML Le Song, Animashree Anandkumar, Bo Dai, Bo Xie
2014	J	`jnl`	Provable Learning of Overcomplete Latent Variable Models: Semi-supervised and Unsupervised Settings. CoRR Animashree Anandkumar, Rong Ge, Majid Janzamin
2014	J	`jnl`	Tensor decompositions for learning latent variable models. J. Mach. Learn. Res. Animashree Anandkumar, Rong Ge, Daniel J. Hsu, Sham M. Kakade, Matus Telgarsky
2013	A*	`conf`	A Tensor Spectral Approach to Learning Mixed Membership Community Models. COLT Animashree Anandkumar, Rong Ge, Daniel J. Hsu, Sham M. Kakade
2013	Misc	`conf`	Active learning of multiple source multiple destination topologies. CISS Pegah Sattari, Maciej Kurant, Animashree Anandkumar, Athina Markopoulou, Michael G. Rabbat
2013	J	`jnl`	Exact Recovery of Sparsely Used Overcomplete Dictionaries. CoRR Alekh Agarwal, Animashree Anandkumar, Praneeth Netrapalli
2013	J	`jnl`	Fast Detection of Overlapping Communities via Online Tensor Methods on GPUs. CoRR Furong Huang, U. N. Niranjan, Mohammad Umar Hakeem, Prateek Verma, Animashree Anandkumar
2013	—	`conf`	Learning Linear Bayesian Networks with Latent Variables. ICML (1) Animashree Anandkumar, Daniel J. Hsu, Adel Javanmard, Sham M. Kakade
2013	J	`jnl`	Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization. CoRR Alekh Agarwal, Animashree Anandkumar, Prateek Jain, Praneeth Netrapalli, Rashish Tandon
2013	J	`jnl`	Nonparametric Estimation of Multi-View Latent Variable Models. CoRR Le Song, Animashree Anandkumar, Bo Dai, Bo Xie
2013	Misc	`conf`	Robust noncooperative rate-maximization game for MIMO Gaussian interference channels under bounded channel uncertainty. ICASSP Amod J. G. Anandkumar, Animashree Anandkumar, Sangarapillai Lambotharan, Jonathon A. Chambers
2013	J	`jnl`	Seeing through black boxes: Tracking transactions through queues under monitoring resource constraints. Perform. Evaluation Animashree Anandkumar, Ting He, Chatschik Bisdikian, Dakshi Agrawal
2013	J	`jnl`	Topology discovery of sparse random graphs with few participants. Random Struct. Algorithms Animashree Anandkumar, Avinatan Hassidim, Jonathan A. Kelner
2013	J	`jnl`	When are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured Sparsity. CoRR Animashree Anandkumar, Daniel J. Hsu, Majid Janzamin, Sham M. Kakade
2012	J	`jnl`	A Method of Moments for Mixture Models and Hidden Markov Models CoRR Animashree Anandkumar, Daniel J. Hsu, Sham M. Kakade
2012	A*	`conf`	A Method of Moments for Mixture Models and Hidden Markov Models. COLT Animashree Anandkumar, Daniel J. Hsu, Sham M. Kakade
2012	J	`jnl`	Active Learning of Multiple Source Multiple Destination Topologies CoRR Pegah Sattari, Maciej Kurant, Animashree Anandkumar, Athina Markopoulou, Michael G. Rabbat
2012	J	`jnl`	Feedback Message Passing for Inference in Gaussian Graphical Models. IEEE Trans. Signal Process. Ying Liu, Venkat Chandrasekaran, Animashree Anandkumar, Alan S. Willsky
2012	A*	`conf`	High-Dimensional Covariance Decomposition into Sparse Markov and Independence Domains. ICML Majid Janzamin, Animashree Anandkumar
2012	J	`jnl`	High-dimensional Gaussian graphical model selection: walk summability and local separation criterion. J. Mach. Learn. Res. Animashree Anandkumar, Vincent Y. F. Tan, Furong Huang, Alan S. Willsky
2012	—	`conf`	Latent Graphical Model Selection: Efficient Methods for Locally Tree-like Graphs. NIPS Animashree Anandkumar, Ragupathyraj Valluvan
2012	J	`jnl`	Learning High-Dimensional Mixtures of Graphical Models CoRR Animashree Anandkumar, Daniel J. Hsu, Sham M. Kakade
2012	J	`jnl`	Learning Linear Bayesian Networks with Latent Variables CoRR Animashree Anandkumar, Daniel J. Hsu, Adel Javanmard, Sham M. Kakade
2012	J	`jnl`	Learning Loopy Graphical Models with Latent Variables: Efficient Methods and Guarantees CoRR Animashree Anandkumar, Ragupathyraj Valluvan
2012	—	`conf`	Learning Mixtures of Tree Graphical Models. NIPS Animashree Anandkumar, Daniel J. Hsu, Furong Huang, Sham M. Kakade
2012	J	`jnl`	Two SVDs Suffice: Spectral decompositions for probabilistic topic modeling and latent Dirichlet allocation CoRR Animashree Anandkumar, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Yi-Kai Liu
2011	J	`jnl`	A Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov Tree Structures. IEEE Trans. Inf. Theory Vincent Y. F. Tan, Animashree Anandkumar, Lang Tong, Alan S. Willsky
2011	J	`jnl`	Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret. IEEE J. Sel. Areas Commun. Animashree Anandkumar, Nithin Michael, Ao Kevin Tang, Ananthram Swami
2011	J	`jnl`	Energy-Latency Tradeoff for In-Network Function Computation in Random Networks CoRR Paul N. Balister, Béla Bollobás, Animashree Anandkumar, Alan S. Willsky
2011	A*	`conf`	Energy-latency tradeoff for in-network function computation in random networks. INFOCOM Paul Balister, Béla Bollobás, Animashree Anandkumar, Alan S. Willsky
2011	J	`jnl`	Feedback Message Passing for Inference in Gaussian Graphical Models CoRR Ying Liu, Venkat Chandrasekaran, Animashree Anandkumar, Alan S. Willsky
2011	J	`jnl`	High-Dimensional Gaussian Graphical Model Selection: Tractable Graph Families CoRR Animashree Anandkumar, Vincent Y. F. Tan, Alan S. Willsky
2011	—	`conf`	High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions. NIPS Animashree Anandkumar, Vincent Y. F. Tan, Alan S. Willsky
2011	J	`jnl`	High-Dimensional Structure Estimation in Ising Models: Tractable Graph Families CoRR Animashree Anandkumar, Vincent Y. F. Tan, Furong Huang, Alan S. Willsky
2011	A*	`conf`	Index-based sampling policies for tracking dynamic networks under sampling constraints. INFOCOM Ting He, Animashree Anandkumar, Dakshi Agrawal
2011	J	`jnl`	Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates. J. Mach. Learn. Res. Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
2011	J	`jnl`	Learning Latent Tree Graphical Models. J. Mach. Learn. Res. Myung Jin Choi, Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
2011	J	`jnl`	Robust Rate Maximization Game Under Bounded Channel Uncertainty. IEEE Trans. Veh. Technol. Amod J. G. Anandkumar, Animashree Anandkumar, Sangarapillai Lambotharan, Jonathon A. Chambers
2011	J	`jnl`	Spectral Methods for Learning Multivariate Latent Tree Structure CoRR Animashree Anandkumar, Kamalika Chaudhuri, Daniel J. Hsu, Sham M. Kakade, Le Song, Tong Zhang
2011	—	`conf`	Spectral Methods for Learning Multivariate Latent Tree Structure. NIPS Animashree Anandkumar, Kamalika Chaudhuri, Daniel J. Hsu, Sham M. Kakade, Le Song, Tong Zhang
2011	J	`jnl`	Summary Based Structures with Improved Sublinear Recovery for Compressed Sensing CoRR M. Amin Khajehnejad, Juhwan Yoo, Animashree Anandkumar, Babak Hassibi
2011	B	`conf`	Summary based structures with improved sublinear recovery for compressed sensing. ISIT M. Amin Khajehnejad, Juhwan Yoo, Animashree Anandkumar, Babak Hassibi
2011	J	`jnl`	Topology Discovery of Sparse Random Graphs With Few Participants CoRR Animashree Anandkumar, Avinatan Hassidim, Jonathan A. Kelner
2011	A*	`conf`	Topology discovery of sparse random graphs with few participants. SIGMETRICS Animashree Anandkumar, Avinatan Hassidim, Jonathan A. Kelner
2010	—	`conf`	Consistent and efficient reconstruction of latent tree models. Allerton Myung Jin Choi, Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
2010	J	`jnl`	Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret CoRR Animashree Anandkumar, Nithin Michael, Ao Kevin Tang, Ananthram Swami
2010	B	`conf`	Error exponents for composite hypothesis testing of Markov forest distributions. ISIT Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
2010	B	`conf`	Feedback message passing for inference in gaussian graphical models. ISIT Ying Liu, Venkat Chandrasekaran, Animashree Anandkumar, Alan S. Willsky
2010	J	`jnl`	Learning Gaussian tree models: analysis of error exponents and extremal structures. IEEE Trans. Signal Process. Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
2010	J	`jnl`	Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates CoRR Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
2010	J	`jnl`	Learning Latent Tree Graphical Models CoRR Myung Jin Choi, Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
2010	B	`conf`	Limit laws for random spatial graphical models. ISIT Animashree Anandkumar, Joseph E. Yukich, Alan S. Willsky
2010	A*	`conf`	Opportunistic Spectrum Access with Multiple Users: Learning under Competition. INFOCOM Animashree Anandkumar, Nithin Michael, Ao Tang
2010	J	`jnl`	Robust Rate-Maximization Game Under Bounded Channel Uncertainty CoRR Amod J. G. Anandkumar, Animashree Anandkumar, Sangarapillai Lambotharan, Jonathon A. Chambers
2010	Misc	`conf`	Robust rate-maximization game under bounded channel uncertainty. ICASSP Amod J. G. Anandkumar, Animashree Anandkumar, Sangarapillai Lambotharan, Jonathon A. Chambers
2010	—	`conf`	Scaling laws for learning high-dimensional Markov forest distributions. Allerton Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
2010	J	`jnl`	Seeing Through Black Boxes : Tracking Transactions through Queues under Monitoring Resource Constraints CoRR Animashree Anandkumar, Ting He, Chatschik Bisdikian, Dakshi Agrawal
2009	J	`jnl`	A Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov Tree Structures CoRR Vincent Y. F. Tan, Animashree Anandkumar, Lang Tong, Alan S. Willsky
2009	B	`conf`	A large-deviation analysis for the maximum likelihood learning of tree structures. ISIT Vincent Y. F. Tan, Animashree Anandkumar, Lang Tong, Alan S. Willsky
2009	B	`conf`	Detection error exponent for spatially dependent samples in random networks. ISIT Animashree Anandkumar, Alan S. Willsky, Lang Tong
2009	J	`jnl`	Detection of Gauss-Markov Random Fields With Nearest-Neighbor Dependency. IEEE Trans. Inf. Theory Animashree Anandkumar, Lang Tong, Ananthram Swami
2009	J	`jnl`	Energy Scaling Laws for Distributed Inference in Random Fusion Networks. IEEE J. Sel. Areas Commun. Animashree Anandkumar, Ananthram Swami, Joseph E. Yukich, Lang Tong
2009	—	`conf`	How do the structure and the parameters of Gaussian tree models affect structure learning? Allerton Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
2009	J	`jnl`	Learning Gaussian Tree Models: Analysis of Error Exponents and Extremal Structures CoRR Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky
2009	A*	`conf`	Prize-Collecting Data Fusion for Cost-Performance Tradeoff in Distributed Inference. INFOCOM Animashree Anandkumar, Meng Wang, Lang Tong, Ananthram Swami
2009	J	`jnl`	Selectively retrofitting monitoring in distributed systems. SIGMETRICS Perform. Evaluation Rev. Animashree Anandkumar, Chatschik Bisdikian, Ting He, Dakshi Agrawal
2008	B	`conf`	Cost-performance tradeoff in multi-hop aggregation for statistical inference. ISIT Animashree Anandkumar, Lang Tong, Ananthram Swami, Anthony Ephremides
2008	J	`jnl`	Distributed Estimation Via Random Access. IEEE Trans. Inf. Theory Animashree Anandkumar, Lang Tong, Ananthram Swami
2008	J	`jnl`	Energy Scaling Laws for Distributed Inference in Random Networks CoRR Animashree Anandkumar, Joseph E. Yukich, Lang Tong, Ananthram Swami
2008	—	`conf`	Min-min times in peer-to-peer file sharing networks. Allerton G. Matthew Ezovski, Animashree Anandkumar, Ao Kevin Tang, Lachlan L. H. Andrew
2008	A*	`conf`	Minimum Cost Data Aggregation with Localized Processing for Statistical Inference. INFOCOM Animashree Anandkumar, Lang Tong, Ananthram Swami, Anthony Ephremides
2008	B	`conf`	Non-intrusive transaction monitoring using system logs. NOMS Bikram Sengupta, Nilanjan Banerjee, Animashree Anandkumar, Chatschik Bisdikian
2008	J	`jnl`	Optimal Node Density for Detection in Energy-Constrained Random Networks. IEEE Trans. Signal Process. Animashree Anandkumar, Lang Tong, Ananthram Swami
2008	A*	`conf`	Tracking in a spaghetti bowl: monitoring transactions using footprints. SIGMETRICS Animashree Anandkumar, Chatschik Bisdikian, Dakshi Agrawal
2007	—	`conf`	Detection of Gauss-Markov Random Field on Nearest-Neighbor Graph. ICASSP (3) Animashree Anandkumar, Lang Tong, Ananthram Swami
2007	J	`jnl`	Detection of Gauss-Markov Random Fields with Nearest-Neighbor Dependency CoRR Animashree Anandkumar, Lang Tong, Ananthram Swami
2007	Misc	`conf`	Energy Efficient Routing for Statistical Inference of Markov Random Fields. CISS Animashree Anandkumar, Lang Tong, Ananthram Swami
2007	J	`jnl`	Type-Based Random Access for Distributed Detection Over Multiaccess Fading Channels. IEEE Trans. Signal Process. Animashree Anandkumar, Lang Tong
2006	—	`conf`	A Large Deviation Analysis of Detection Over Multi-Access Channels with Random Number of Sensors. ICASSP (4) Animashree Anandkumar, Lang Tong
2006	Misc	`conf`	Distributed Statistical Inference using Type Based Random Access over Multi-access Fading Channels. CISS Animashree Anandkumar, Lang Tong