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DORO: Distributional and Outlier Robust Optimization


Jun 11, 2021
Runtian Zhai, Chen Dan, J. Zico Kolter, Pradeep Ravikumar

* ICML 2021. Codes: https://github.com/RuntianZ/doro 

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Iterative Barycenter Flows


Apr 15, 2021
David I. Inouye, Zeyu Zhou, Ziyu Gong, Pradeep Ravikumar


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Contrastive learning of strong-mixing continuous-time stochastic processes


Mar 03, 2021
Bingbin Liu, Pradeep Ravikumar, Andrej Risteski

* Appearing in AISTATS 2021 

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An Online Learning Approach to Interpolation and Extrapolation in Domain Generalization


Feb 25, 2021
Elan Rosenfeld, Pradeep Ravikumar, Andrej Risteski


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On Proximal Policy Optimization's Heavy-tailed Gradients


Feb 20, 2021
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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When Is Generalizable Reinforcement Learning Tractable?


Jan 01, 2021
Dhruv Malik, Yuanzhi Li, Pradeep Ravikumar

* 34 pages. 4 figures 

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Fundamental Limits and Tradeoffs in Invariant Representation Learning


Dec 19, 2020
Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar


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The Risks of Invariant Risk Minimization


Oct 12, 2020
Elan Rosenfeld, Pradeep Ravikumar, Andrej Risteski


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Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification


Jun 29, 2020
Chen Dan, Yuting Wei, Pradeep Ravikumar

* 25 pages, 1 figure. Accepted by ICML 2020 

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Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances


Jun 24, 2020
Sijie He, Xinyan Li, Timothy DelSole, Pradeep Ravikumar, Arindam Banerjee


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Learning Minimax Estimators via Online Learning


Jun 19, 2020
Kartik Gupta, Arun Sai Suggala, Adarsh Prasad, Praneeth Netrapalli, Pradeep Ravikumar

* 60 pages. Under review 

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Evaluations and Methods for Explanation through Robustness Analysis


May 31, 2020
Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh


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Class-Weighted Classification: Trade-offs and Robust Approaches


May 26, 2020
Ziyu Xu, Chen Dan, Justin Khim, Pradeep Ravikumar

* 28 pages, 4 figures 

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Minimizing FLOPs to Learn Efficient Sparse Representations


Apr 12, 2020
Biswajit Paria, Chih-Kuan Yeh, Ian E. H. Yen, Ning Xu, Pradeep Ravikumar, Barnabás Póczos

* Published at ICLR 2020 

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MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius


Feb 15, 2020
Runtian Zhai, Chen Dan, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho-Jui Hsieh, Liwei Wang

* In ICLR 2020. 20 Pages 

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Certified Robustness to Label-Flipping Attacks via Randomized Smoothing


Feb 07, 2020
Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar, J. Zico Kolter


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Game Design for Eliciting Distinguishable Behavior


Dec 12, 2019
Fan Yang, Liu Leqi, Yifan Wu, Zachary C. Lipton, Pradeep Ravikumar, William W. Cohen, Tom Mitchell

* 33rd Conference on Neural Information Processing Systems (NeurIPS 2019) 

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Diagnostic Curves for Black Box Models


Dec 02, 2019
David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar

* Accepted to NeurIPS 2019 Workshop on Safety and Robustness in Decision Making 

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Optimal Analysis of Subset-Selection Based L_p Low Rank Approximation


Oct 30, 2019
Chen Dan, Hong Wang, Hongyang Zhang, Yuchen Zhou, Pradeep Ravikumar

* 20 pages, accepted by NeurIPS 2019 

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On Concept-Based Explanations in Deep Neural Networks


Oct 17, 2019
Chih-Kuan Yeh, Been Kim, Sercan O. Arik, Chun-Liang Li, Pradeep Ravikumar, Tomas Pfister


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Learning Sparse Nonparametric DAGs


Sep 29, 2019
Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

* 17 pages, 5 figures 

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A Unified Approach to Robust Mean Estimation


Jul 01, 2019
Adarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar

* 51 pages, 6 figures 

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Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression


Mar 19, 2019
Arun Sai Suggala, Kush Bhatia, Pradeep Ravikumar, Prateek Jain


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How Sensitive are Sensitivity-Based Explanations?


Jan 27, 2019
Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David Inouye, Pradeep Ravikumar


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Towards Aggregating Weighted Feature Attributions


Jan 20, 2019
Umang Bhatt, Pradeep Ravikumar, Jose M. F. Moura

* In AAAI-19 Workshop on Network Interpretability for Deep Learning 

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Representer Point Selection for Explaining Deep Neural Networks


Nov 23, 2018
Chih-Kuan Yeh, Joon Sik Kim, Ian E. H. Yen, Pradeep Ravikumar

* NIPS 2018 

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DAGs with NO TEARS: Continuous Optimization for Structure Learning


Nov 03, 2018
Xun Zheng, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

* 22 pages, 8 figures, accepted to NIPS 2018 

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