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Leveraging Unlabeled Data to Predict Out-of-Distribution Performance



Saurabh Garg , Sivaraman Balakrishnan , Zachary C. Lipton , Behnam Neyshabur , Hanie Sedghi

* Accepted at ICLR 2022 

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Minimax Optimal Regression over Sobolev Spaces via Laplacian Eigenmaps on Neighborhood Graphs



Alden Green , Sivaraman Balakrishnan , Ryan J. Tibshirani

* 59 pages 

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Mixture Proportion Estimation and PU Learning: A Modern Approach



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

* Spotlight at NeurIPS 2021 

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Heavy-tailed Streaming Statistical Estimation



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


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Plugin Estimation of Smooth Optimal Transport Maps



Tudor Manole , Sivaraman Balakrishnan , Jonathan Niles-Weed , Larry Wasserman


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



Alden Green , Sivaraman Balakrishnan , Ryan J. Tibshirani


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RATT: Leveraging Unlabeled Data to Guarantee Generalization



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

* Pre-print 

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On Proximal Policy Optimization's Heavy-tailed Gradients



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

* Pre-print 

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



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

* 36 pages, 4 figures 

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