Animashree Anandkumar
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
67
Venues
21
Active years
2006–2024
Best venue rank
A*
Where they publish
- A*ICML16 papers
- A*COLT7 papers
- BISIT7 papers
- A*ICLR5 papers
- A*INFOCOM5 papers
- MulticonferenceICASSP4 papers
- AAISTATS3 papers
- A*ICRA3 papers
- NationalCISS3 papers
- NationalHiPC2 papers
- A*SIGMETRICS2 papers
- AWACV1 paper
- A*IJCAI1 paper
- A*AAAI1 paper
- A*ICCV1 paper
- BDCC1 paper
- AUAI1 paper
- A*ECCV1 paper
- NationalITA1 paper
- A*ICDM1 paper
- BNOMS1 paper
Papers
67 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | WACV | Differentially Private Video Activity Recognition. | Zelun Luo, Yuliang Zou, Yijin Yang, Zane Durante, De-An Huang, Zhiding Yu, Chaowei Xiao, Li Fei-Fei, Animashree Anandkumar |
| 2023 | AISTATS | Distributionally Robust Policy Gradient for Offline Contextual Bandits. | Zhouhao Yang, Yihong Guo, Pan Xu, Anqi Liu, Animashree Anandkumar |
| 2023 | IJCAI | Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach. | Haoxuan Wang, Zhiding Yu, Yisong Yue, Animashree Anandkumar, Anqi Liu, Junchi Yan |
| 2022 | AISTATS | Reinforcement Learning with Fast Stabilization in Linear Dynamical Systems. | Sahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Animashree Anandkumar |
| 2022 | COLT | Thompson Sampling Achieves $\tilde{O}(\sqrt{T})$ Regret in Linear Quadratic Control. | Taylan Kargin, Sahin Lale, Kamyar Azizzadenesheli, Animashree Anandkumar, Babak Hassibi |
| 2022 | ICML | Langevin Monte Carlo for Contextual Bandits. | Pan Xu, Hongkai Zheng, Eric V. Mazumdar, Kamyar Azizzadenesheli, Animashree Anandkumar |
| 2022 | ICML | Diffusion Models for Adversarial Purification. | Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Animashree Anandkumar |
| 2022 | ICML | Understanding The Robustness in Vision Transformers. | Daquan Zhou, Zhiding Yu, Enze Xie, Chaowei Xiao, Animashree Anandkumar, Jiashi Feng, Jos M. lvarez |
| 2021 | AAAI | Deep Bayesian Quadrature Policy Optimization. | Ravi Tej Akella, Kamyar Azizzadenesheli, Mohammad Ghavamzadeh, Animashree Anandkumar, Yisong Yue |
| 2021 | AISTATS | Active Learning under Label Shift. | Eric Zhao, Anqi Liu, Animashree Anandkumar, Yisong Yue |
| 2021 | ICCV | Self-Calibrating Neural Radiance Fields. | Yoonwoo Jeong, Seokjun Ahn, Christopher B. Choy, Animashree Anandkumar, Minsu Cho, Jaesik Park |
| 2021 | ICML | Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection. | Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Animashree Anandkumar, Sanja Fidler, Jos M. lvarez |
| 2021 | ICML | SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies. | Linxi Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Animashree Anandkumar |
| 2021 | ICML | Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning. | Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar |
| 2021 | ICRA | Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objects. | Xinlei Pan, Animesh Garg, Animashree Anandkumar, Yuke Zhu |
| 2021 | ICRA | Fast Uncertainty Quantification for Deep Object Pose Estimation. | Guanya Shi, Yifeng Zhu, Jonathan Tremblay, Stan Birchfield, Fabio Ramos, Animashree Anandkumar, Yuke Zhu |
| 2020 | DCC | Higher-Order Count Sketch: Dimensionality Reduction that Retains Efficient Tensor Operations. | Yang Shi, Animashree Anandkumar |
| 2020 | HiPC | Role of HPC in next-generation AI. | Animashree Anandkumar |
| 2020 | ICML | Angular Visual Hardness. | Beidi Chen, Weiyang Liu, Zhiding Yu, Jan Kautz, Anshumali Shrivastava, Animesh Garg, Animashree Anandkumar |
| 2020 | ICML | Automated Synthetic-to-Real Generalization. | Wuyang Chen, Zhiding Yu, Zhangyang Wang, Animashree Anandkumar |
| 2020 | ICML | Semi-Supervised StyleGAN for Disentanglement Learning. | Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Animashree Anandkumar |
| 2020 | ICML | Implicit competitive regularization in GANs. | Florian Schfer, Hongkai Zheng, Animashree Anandkumar |
| 2020 | UAI | OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation. | Hongyu Ren, Yuke Zhu, Jure Leskovec, Animashree Anandkumar, Animesh Garg |
| 2019 | ICLR | Regularized Learning for Domain Adaptation under Label Shifts. | Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar |
| 2019 | ICML | Open Vocabulary Learning on Source Code with a Graph-Structured Cache. | Milan Cvitkovic, Badal Singh, Animashree Anandkumar |
| 2019 | ICRA | Neural Lander: Stable Drone Landing Control Using Learned Dynamics. | Guanya Shi, Xichen Shi, Michael O'Connell, Rose Yu, Kamyar Azizzadenesheli, Animashree Anandkumar, Yisong Yue, Soon-Jo Chung |
| 2018 | ECCV | Question Type Guided Attention in Visual Question Answering. | Yang Shi, Tommaso Furlanello, Sheng Zha, Animashree Anandkumar |
| 2018 | ICLR | Combining Symbolic Expressions and Black-box Function Evaluations in Neural Programs. | Forough Arabshahi, Sameer Singh, Animashree Anandkumar |
| 2018 | ICLR | Stochastic Activation Pruning for Robust Adversarial Defense. | Guneet S. Dhillon, Kamyar Azizzadenesheli, Zachary C. Lipton, Jeremy Bernstein, Jean Kossaifi, Aran Khanna, Animashree Anandkumar |
| 2018 | ICLR | Learning From Noisy Singly-labeled Data. | Ashish Khetan, Zachary C. Lipton, Animashree Anandkumar |
| 2018 | ICLR | Deep Active Learning for Named Entity Recognition. | Yanyao Shen, Hyokun Yun, Zachary C. Lipton, Yakov Kronrod, Animashree Anandkumar |
| 2018 | ICML | SIGNSGD: Compressed Optimisation for Non-Convex Problems. | Jeremy Bernstein, Yu-Xiang Wang, Kamyar Azizzadenesheli, Animashree Anandkumar |
| 2018 | ICML | StrassenNets: Deep Learning with a Multiplication Budget. | Michael Tschannen, Aran Khanna, Animashree Anandkumar |
| 2018 | ITA | Efficient Exploration Through Bayesian Deep Q-Networks. | Kamyar Azizzadenesheli, Emma Brunskill, Animashree Anandkumar |
| 2016 | COLT | Efficient approaches for escaping higher order saddle points in non-convex optimization. | Animashree Anandkumar, Rong Ge |
| 2016 | COLT | Reinforcement Learning of POMDPs using Spectral Methods. | Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar |
| 2016 | COLT | Open Problem: Approximate Planning of POMDPs in the class of Memoryless Policies. | Kamyar Azizzadenesheli, Alessandro Lazaric, Animashree Anandkumar |
| 2016 | HiPC | Tensor Contractions with Extended BLAS Kernels on CPU and GPU. | Yang Shi, U. N. Niranjan, Animashree Anandkumar, Cris Cecka |
| 2015 | COLT | Learning Overcomplete Latent Variable Models through Tensor Methods. | Animashree Anandkumar, Rong Ge, Majid Janzamin |
| 2015 | ICDM | 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, Carter T. Butts, Sean M. Fitzhugh |
| 2014 | COLT | Learning Sparsely Used Overcomplete Dictionaries. | Alekh Agarwal, Animashree Anandkumar, Prateek Jain, Praneeth Netrapalli, Rashish Tandon |
| 2014 | ICML | Nonparametric Estimation of Multi-View Latent Variable Models. | Le Song, Animashree Anandkumar, Bo Dai, Bo Xie |
| 2013 | CISS | Active learning of multiple source multiple destination topologies. | Pegah Sattari, Maciej Kurant, Animashree Anandkumar, Athina Markopoulou, Michael G. Rabbat |
| 2013 | COLT | A Tensor Spectral Approach to Learning Mixed Membership Community Models. | Animashree Anandkumar, Rong Ge, Daniel J. Hsu, Sham M. Kakade |
| 2013 | ICASSP | Robust noncooperative rate-maximization game for MIMO Gaussian interference channels under bounded channel uncertainty. | Amod J. G. Anandkumar, Animashree Anandkumar, Sangarapillai Lambotharan, Jonathon A. Chambers |
| 2013 | ICML | Learning Linear Bayesian Networks with Latent Variables. | Animashree Anandkumar, Daniel J. Hsu, Adel Javanmard, Sham M. Kakade |
| 2012 | ICML | High-Dimensional Covariance Decomposition into Sparse Markov and Independence Domains. | Majid Janzamin, Animashree Anandkumar |
| 2011 | INFOCOM | Energy-latency tradeoff for in-network function computation in random networks. | Paul Balister, Bla Bollobs, Animashree Anandkumar, Alan S. Willsky |
| 2011 | INFOCOM | Index-based sampling policies for tracking dynamic networks under sampling constraints. | Ting He, Animashree Anandkumar, Dakshi Agrawal |
| 2011 | ISIT | Summary based structures with improved sublinear recovery for compressed sensing. | M. Amin Khajehnejad, Juhwan Yoo, Animashree Anandkumar, Babak Hassibi |
| 2011 | SIGMETRICS | Topology discovery of sparse random graphs with few participants. | Animashree Anandkumar, Avinatan Hassidim, Jonathan A. Kelner |
| 2010 | ICASSP | Robust rate-maximization game under bounded channel uncertainty. | Amod J. G. Anandkumar, Animashree Anandkumar, Sangarapillai Lambotharan, Jonathon A. Chambers |
| 2010 | INFOCOM | Opportunistic Spectrum Access with Multiple Users: Learning under Competition. | Animashree Anandkumar, Nithin Michael, Ao Tang |
| 2010 | ISIT | Limit laws for random spatial graphical models. | Animashree Anandkumar, Joseph E. Yukich, Alan S. Willsky |
| 2010 | ISIT | Feedback message passing for inference in gaussian graphical models. | Ying Liu, Venkat Chandrasekaran, Animashree Anandkumar, Alan S. Willsky |
| 2010 | ISIT | Error exponents for composite hypothesis testing of Markov forest distributions. | Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky |
| 2009 | INFOCOM | Prize-Collecting Data Fusion for Cost-Performance Tradeoff in Distributed Inference. | Animashree Anandkumar, Meng Wang, Lang Tong, Ananthram Swami |
| 2009 | ISIT | Detection error exponent for spatially dependent samples in random networks. | Animashree Anandkumar, Alan S. Willsky, Lang Tong |
| 2009 | ISIT | A large-deviation analysis for the maximum likelihood learning of tree structures. | Vincent Y. F. Tan, Animashree Anandkumar, Lang Tong, Alan S. Willsky |
| 2008 | INFOCOM | Minimum Cost Data Aggregation with Localized Processing for Statistical Inference. | Animashree Anandkumar, Lang Tong, Ananthram Swami, Anthony Ephremides |
| 2008 | ISIT | Cost-performance tradeoff in multi-hop aggregation for statistical inference. | Animashree Anandkumar, Lang Tong, Ananthram Swami, Anthony Ephremides |
| 2008 | NOMS | Non-intrusive transaction monitoring using system logs. | Bikram Sengupta, Nilanjan Banerjee, Animashree Anandkumar, Chatschik Bisdikian |
| 2008 | SIGMETRICS | Tracking in a spaghetti bowl: monitoring transactions using footprints. | Animashree Anandkumar, Chatschik Bisdikian, Dakshi Agrawal |
| 2007 | CISS | Energy Efficient Routing for Statistical Inference of Markov Random Fields. | Animashree Anandkumar, Lang Tong, Ananthram Swami |
| 2007 | ICASSP | Detection of Gauss-Markov Random Field on Nearest-Neighbor Graph. | Animashree Anandkumar, Lang Tong, Ananthram Swami |
| 2006 | CISS | Distributed Statistical Inference using Type Based Random Access over Multi-access Fading Channels. | Animashree Anandkumar, Lang Tong |
| 2006 | ICASSP | A Large Deviation Analysis of Detection Over Multi-Access Channels with Random Number of Sensors. | Animashree Anandkumar, Lang Tong |