Balakrishnan, Sivaraman

41 publications

NeurIPS 2023 Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift Saurabh Garg, Amrith Setlur, Zachary Lipton, Sivaraman Balakrishnan, Virginia Smith, Aditi Raghunathan

AISTATS 2023 Domain Adaptation Under Missingness Shift Helen Zhou, Sivaraman Balakrishnan, Zachary Lipton

NeurIPS 2023 Online Label Shift: Optimal Dynamic Regret Meets Practical Algorithms Dheeraj Baby, Saurabh Garg, Tzu-Ching Yen, Sivaraman Balakrishnan, Zachary Lipton, Yu-Xiang Wang

ICML 2023 RLSbench: Domain Adaptation Under Relaxed Label Shift Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary Chase Lipton

AISTATS 2022 Heavy-Tailed Streaming Statistical Estimation Che-Ping Tsai, Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar

NeurIPS 2022 Domain Adaptation Under Open Set Label Shift Saurabh Garg, Sivaraman Balakrishnan, Zachary Lipton

ICMLW 2022 Domain Adaptation Under Open Set Label Shift Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton

ICLR 2022 Leveraging Unlabeled Data to Predict Out-of-Distribution Performance Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton, Behnam Neyshabur, Hanie Sedghi

NeurIPSW 2022 RLSBench: A Large-Scale Empirical Study of Domain Adaptation Under Relaxed Label Shift Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary Chase Lipton

JMLR 2022 Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh

ALT 2022 Understanding Simultaneous Train and Test Robustness Pranjal Awasthi, Sivaraman Balakrishnan, Aravindan Vijayaraghavan

AISTATS 2021 Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs Alden Green, Sivaraman Balakrishnan, Ryan Tibshirani

NeurIPSW 2021 Leveraging Unlabeled Data to Predict Out-of-Distribution Performance Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton, Behnam Neyshabur, Hanie Sedghi

NeurIPS 2021 Mixture Proportion Estimation and PU Learning:A Modern Approach Saurabh Garg, Yifan Wu, Alexander J Smola, Sivaraman Balakrishnan, Zachary Lipton

ICML 2021 On Proximal Policy Optimization’s Heavy-Tailed Gradients Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, Zico Kolter, Zachary Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar

JMLR 2021 Path Length Bounds for Gradient Descent and Flow Chirag Gupta, Sivaraman Balakrishnan, Aaditya Ramdas

ICML 2021 RATT: Leveraging Unlabeled Data to Guarantee Generalization Saurabh Garg, Sivaraman Balakrishnan, Zico Kolter, Zachary Lipton

JMLR 2021 Statistical Guarantees for Local Spectral Clustering on Random Neighborhood Graphs Alden Green, Sivaraman Balakrishnan, Ryan J. Tibshirani

AISTATS 2020 A Robust Univariate Mean Estimator Is All You Need Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar

NeurIPS 2020 A Unified View of Label Shift Estimation Saurabh Garg, Yifan Wu, Sivaraman Balakrishnan, Zachary Lipton

NeurIPS 2020 On Learning Ising Models Under Huber's Contamination Model Adarsh Prasad, Vishwak Srinivasan, Sivaraman Balakrishnan, Pradeep K. Ravikumar

JMLR 2020 Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski

JMLR 2019 Low Permutation-Rank Matrices: Structural Properties and Noisy Completion Nihar B. Shah, Sivaraman Balakrishnan, Martin J. Wainwright

NeurIPS 2018 How Many Samples Are Needed to Estimate a Convolutional Neural Network? Simon S Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh

ICML 2018 Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski

NeurIPS 2018 Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates Yining Wang, Sivaraman Balakrishnan, Aarti Singh

AISTATS 2018 Stochastic Zeroth-Order Optimization in High Dimensions Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh

COLT 2017 Computationally Efficient Robust Sparse Estimation in High Dimensions Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh

JMLR 2017 Statistical and Computational Guarantees for the Baum-Welch Algorithm Fanny Yang, Sivaraman Balakrishnan, Martin J. Wainwright

JMLR 2016 Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence Nihar B. Shah, Sivaraman Balakrishnan, Joseph Bradley, Abhay Parekh, Kannan Ramchandran, Martin J. Wainwright

NeurIPS 2016 Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences Chi Jin, Yuchen Zhang, Sivaraman Balakrishnan, Martin J. Wainwright, Michael I Jordan

NeurIPS 2016 Statistical Inference for Cluster Trees Jisu Kim, Yen-Chi Chen, Sivaraman Balakrishnan, Alessandro Rinaldo, Larry Wasserman

ICML 2016 Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues Nihar Shah, Sivaraman Balakrishnan, Aditya Guntuboyina, Martin Wainwright

AISTATS 2015 Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence Nihar B. Shah, Sivaraman Balakrishnan, Joseph K. Bradley, Abhay Parekh, Kannan Ramchandran, Martin J. Wainwright

NeurIPS 2013 Cluster Trees on Manifolds Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, Larry Wasserman

ICML 2012 Efficient Active Algorithms for Hierarchical Clustering Akshay Krishnamurthy, Sivaraman Balakrishnan, Min Xu, Aarti Singh

AISTATS 2012 Minimax Rates for Homology Inference Sivaraman Balakrishnan, Alesandro Rinaldo, Don Sheehy, Aarti Singh, Larry Wasserman

NeurIPS 2012 Optimal Kernel Choice for Large-Scale Two-Sample Tests Arthur Gretton, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu, Bharath K. Sriperumbudur

ICML 2012 Sparse Additive Functional and Kernel CCA Sivaraman Balakrishnan, Kriti Puniyani, John D. Lafferty

NeurIPS 2011 Minimax Localization of Structural Information in Large Noisy Matrices Mladen Kolar, Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh

NeurIPS 2011 Noise Thresholds for Spectral Clustering Sivaraman Balakrishnan, Min Xu, Akshay Krishnamurthy, Aarti Singh