Sivaraman Balakrishnan

According to our database, Sivaraman Balakrishnan authored at least 58 papers between 2009 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift.

Saurabh Garg, Amrith Setlur, Zachary C. Lipton, Sivaraman Balakrishnan, Virginia Smith, Aditi Raghunathan

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms.

Dheeraj Baby, Saurabh Garg, Tzu-Ching Yen, Sivaraman Balakrishnan, Zachary C. Lipton, Yu-Xiang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

RLSbench: Domain Adaptation Under Relaxed Label Shift.

Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary Chase Lipton

Proceedings of the International Conference on Machine Learning, 2023

Domain Adaptation under Missingness Shift.

Helen Zhou, Sivaraman Balakrishnan, Zachary C. Lipton

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions.

Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh

J. Mach. Learn. Res., 2022

Domain Adaptation under Open Set Label Shift.

Saurabh Garg, Sivaraman Balakrishnan, Zachary C. Lipton

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

No Rose for MLE: Inadmissibility of MLE for Evaluation Aggregation Under Levels of Expertise.

Charvi Rastogi, Ivan Stelmakh, Nihar B. Shah, Sivaraman Balakrishnan

Proceedings of the IEEE International Symposium on Information Theory, 2022

Leveraging unlabeled data to predict out-of-distribution performance.

Saurabh Garg, Sivaraman Balakrishnan, Zachary Chase Lipton, Behnam Neyshabur, Hanie Sedghi

Proceedings of the Tenth International Conference on Learning Representations, 2022

Understanding Simultaneous Train and Test Robustness.

Pranjal Awasthi, Sivaraman Balakrishnan, Aravindan Vijayaraghavan

Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

Heavy-tailed Streaming Statistical Estimation.

Che-Ping Tsai, Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

A Permutation-Based Model for Crowd Labeling: Optimal Estimation and Robustness.

Nihar B. Shah, Sivaraman Balakrishnan, Martin J. Wainwright

IEEE Trans. Inf. Theory, 2021

Path Length Bounds for Gradient Descent and Flow.

Chirag Gupta, Sivaraman Balakrishnan, Aaditya Ramdas

J. Mach. Learn. Res., 2021

Statistical Guarantees for Local Spectral Clustering on Random Neighborhood Graphs.

Alden Green, Sivaraman Balakrishnan, Ryan J. Tibshirani

J. Mach. Learn. Res., 2021

Mixture Proportion Estimation and PU Learning: A Modern Approach.

Saurabh Garg, Yifan Wu, Alexander J. Smola, Sivaraman Balakrishnan, Zachary C. Lipton

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Proximal Policy Optimization's Heavy-tailed Gradients.

Saurabh Garg, Joshua Zhanson, Emilio Parisotto, Adarsh Prasad, J. Zico Kolter, Zachary C. Lipton, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Pradeep Ravikumar

Proceedings of the 38th International Conference on Machine Learning, 2021

RATT: Leveraging Unlabeled Data to Guarantee Generalization.

Saurabh Garg, Sivaraman Balakrishnan, J. Zico Kolter, Zachary C. Lipton

Proceedings of the 38th International Conference on Machine Learning, 2021

Minimax Optimal Regression over Sobolev Spaces via Laplacian Regularization on Neighborhood Graphs.

Alden Green, Sivaraman Balakrishnan, Ryan J. Tibshirani

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information.

Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski

J. Mach. Learn. Res., 2020

On Learning Ising Models under Huber's Contamination Model.

Adarsh Prasad, Vishwak Srinivasan, Sivaraman Balakrishnan, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Unified View of Label Shift Estimation.

Saurabh Garg, Yifan Wu, Sivaraman Balakrishnan, Zachary C. Lipton

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Two-Sample Testing on Pairwise Comparison Data and the Role of Modeling Assumptions.

Charvi Rastogi, Sivaraman Balakrishnan, Nihar B. Shah, Aarti Singh

Proceedings of the IEEE International Symposium on Information Theory, 2020

A Robust Univariate Mean Estimator is All You Need.

Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Optimization of Smooth Functions With Noisy Observations: Local Minimax Rates.

Yining Wang, Sivaraman Balakrishnan, Aarti Singh

IEEE Trans. Inf. Theory, 2019

Feeling the Bern: Adaptive Estimators for Bernoulli Probabilities of Pairwise Comparisons.

Nihar B. Shah, Sivaraman Balakrishnan, Martin J. Wainwright

IEEE Trans. Inf. Theory, 2019

Rate optimal estimation and confidence intervals for high-dimensional regression with missing covariates.

Yining Wang, Jialei Wang, Sivaraman Balakrishnan, Aarti Singh

J. Multivar. Anal., 2019

Low Permutation-rank Matrices: Structural Properties and Noisy Completion.

Nihar B. Shah, Sivaraman Balakrishnan, Martin J. Wainwright

J. Mach. Learn. Res., 2019

A Unified Approach to Robust Mean Estimation.

Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar

CoRR, 2019

2018

Robust Nonparametric Regression under Huber's ε-contamination Model.

Simon S. Du, Yining Wang, Sivaraman Balakrishnan, Pradeep Ravikumar, Aarti Singh

CoRR, 2018

How Many Samples are Needed to Learn a Convolutional Neural Network?

Simon S. Du, Yining Wang, Xiyu Zhai, Sivaraman Balakrishnan, Ruslan Salakhutdinov, Aarti Singh

CoRR, 2018

Robust Estimation via Robust Gradient Estimation.

Adarsh Prasad, Arun Sai Suggala, Sivaraman Balakrishnan, Pradeep Ravikumar

CoRR, 2018

Local White Matter Architecture Defines Functional Brain Dynamics.

Sivaraman Balakrishnan, Yo Joong Choe, Aarti Singh, Jean M. Vettel, Timothy D. Verstynen

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 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

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information.

Yichong Xu, Hariank Muthakana, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski

Proceedings of the 35th International Conference on Machine Learning, 2018

Stochastic Zeroth-order Optimization in High Dimensions.

Yining Wang, Simon S. Du, Sivaraman Balakrishnan, Aarti Singh

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Interactive Linear Regression with Pairwise Comparisons.

Yichong Xu, Sivaraman Balakrishnan, Aarti Singh, Artur Dubrawski

Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017

Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues.

Nihar B. Shah, Sivaraman Balakrishnan, Adityanand Guntuboyina, Martin J. Wainwright

IEEE Trans. Inf. Theory, 2017

Statistical and Computational Guarantees for the Baum-Welch Algorithm.

Fanny Yang, Sivaraman Balakrishnan, Martin J. Wainwright

J. Mach. Learn. Res., 2017

Hypothesis Testing for High-Dimensional Multinomials: A Selective Review.

Sivaraman Balakrishnan, Larry A. Wasserman

CoRR, 2017

Computationally Efficient Robust Estimation of Sparse Functionals.

Simon S. Du, Sivaraman Balakrishnan, Aarti Singh

CoRR, 2017

Hypothesis Testing For Densities and High-Dimensional Multinomials: Sharp Local Minimax Rates.

Sivaraman Balakrishnan, Larry A. Wasserman

CoRR, 2017

Biases in Data-Driven Networking, and What to Do About Them.

Mihovil Bartulovic, Junchen Jiang, Sivaraman Balakrishnan, Vyas Sekar, Bruno Sinopoli

Proceedings of the 16th ACM Workshop on Hot Topics in Networks, Palo Alto, CA, USA, 2017

Computationally Efficient Robust Sparse Estimation in High Dimensions.

Sivaraman Balakrishnan, Simon S. Du, Jerry Li, Aarti Singh

Proceedings of the 30th Conference on Learning Theory, 2017

2016

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

J. Mach. Learn. Res., 2016

Arbitrage-Free Combinatorial Market Making via Integer Programming.

Christian Kroer, Miroslav Dudík, Sébastien Lahaie, Sivaraman Balakrishnan

Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

Statistical Inference for Cluster Trees.

Jisu Kim, Yen-Chi Chen, Sivaraman Balakrishnan, Alessandro Rinaldo, Larry A. Wasserman

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 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

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2014

When is it Better to Compare than to Score?

Nihar B. Shah, Sivaraman Balakrishnan, Joseph K. Bradley, Abhay Parekh, Kannan Ramchandran, Martin J. Wainwright

CoRR, 2014

Statistical guarantees for the EM algorithm: From population to sample-based analysis.

Sivaraman Balakrishnan, Martin J. Wainwright, Bin Yu

CoRR, 2014

2013

Statistical Inference For Persistent Homology

Sivaraman Balakrishnan, Brittany Fasy, Fabrizio Lecci, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman

CoRR, 2013

Tight Lower Bounds for Homology Inference.

Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman

CoRR, 2013

Cluster Trees on Manifolds.

Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh, Larry A. Wasserman

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Minimax rates for homology inference.

Sivaraman Balakrishnan, Alessandro Rinaldo, Don Sheehy, Aarti Singh, Larry A. Wasserman

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Optimal kernel choice for large-scale two-sample tests.

Arthur Gretton, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Efficient Active Algorithms for Hierarchical Clustering.

Akshay Krishnamurthy, Sivaraman Balakrishnan, Min Xu, Aarti Singh

Proceedings of the 29th International Conference on Machine Learning, 2012

Sparse Additive Functional and Kernel CCA.

Sivaraman Balakrishnan, Kriti Puniyani, John D. Lafferty

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Minimax Localization of Structural Information in Large Noisy Matrices.

Mladen Kolar, Sivaraman Balakrishnan, Alessandro Rinaldo, Aarti Singh

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Noise Thresholds for Spectral Clustering.

Sivaraman Balakrishnan, Min Xu, Akshay Krishnamurthy, Aarti Singh

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2009

Communication interception of human signal transduction pathways by Human Immunodeficiency Virus-1.

Sivaraman Balakrishnan, Öznur Tastan, Jaime G. Carbonell, Judith Klein-Seetharaman

Proceedings of the 2009 IEEE International Workshop on Genomic Signal Processing and Statistics, 2009