Sivaraman Balakrishnan

Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift NeurIPS 2023 Domain Adaptation under Missingness Shift AISTATS 2023 Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms NeurIPS 2023 RLSbench: Domain Adaptation Under Relaxed Label Shift ICML 2023 Domain Adaptation under Open Set Label Shift NeurIPS 2022 Heavy-tailed Streaming Statistical Estimation AISTATS 2022 Leveraging unlabeled data to predict out-of-distribution performance ICLR 2022 Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions JMLR 2022 Understanding Simultaneous Train and Test Robustness ALT 2022 Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs AISTATS 2021 Mixture Proportion Estimation and PU Learning:A Modern Approach NeurIPS 2021 On Proximal Policy Optimization’s Heavy-tailed Gradients ICML 2021 Path Length Bounds for Gradient Descent and Flow JMLR 2021 RATT: Leveraging Unlabeled Data to Guarantee Generalization ICML 2021 Statistical Guarantees for Local Spectral Clustering on Random Neighborhood Graphs JMLR 2021 A Robust Univariate Mean Estimator is All You Need AISTATS 2020 A Unified View of Label Shift Estimation NeurIPS 2020 On Learning Ising Models under Huber's Contamination Model NeurIPS 2020 Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information JMLR 2020 Low Permutation-rank Matrices: Structural Properties and Noisy Completion JMLR 2019 How Many Samples are Needed to Estimate a Convolutional Neural Network? NeurIPS 2018 Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information ICML 2018 Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates NeurIPS 2018 Stochastic Zeroth-order Optimization in High Dimensions AISTATS 2018 Computationally Efficient Robust Sparse Estimation in High Dimensions COLT 2017 Statistical and Computational Guarantees for the Baum-Welch Algorithm JMLR 2017 Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence JMLR 2016 Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences NeurIPS 2016 Statistical Inference for Cluster Trees NeurIPS 2016 Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues ICML 2016 Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence AISTATS 2015 Cluster Trees on Manifolds NeurIPS 2013 Minimax rates for homology inference AISTATS 2012 Optimal kernel choice for large-scale two-sample tests NeurIPS 2012 Minimax Localization of Structural Information in Large Noisy Matrices NeurIPS 2011 Noise Thresholds for Spectral Clustering NeurIPS 2011