Pradeep Ravikumar

Associate Professor

Machine Learning Department, School of Computer Science, Carnegie Mellon University

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I lead the Foundations of Statistical Machine Learning Group in the Machine Learning Department, School of Computer Science at Carnegie Mellon University.

Papers167 papers

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The Risks of Invariant Risk Minimization

Elan Rosenfeld,Pradeep Ravikumar, Andrej Risteski

ICLR 2021, (2021)

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Evaluations and Methods for Explanation through Robustness Analysis

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

ICLR 2021, (2021)

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Certified Robustness to Label-Flipping Attacks via Randomized Smoothing

Rosenfeld Elan, Winston Ezra,Ravikumar Pradeep,Kolter J. Zico

ICML, pp.8230-8241, (2020)

Cited by1EIBibtex

Fundamental Limits and Tradeoffs in Invariant Representation Learning

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

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Optimal Statistical Guaratees for Adversarially Robust Gaussian Classification

Chen Dan,Yuting Wei,Pradeep Ravikumar

international conference on machine learning, (2020)

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Robust Estimation via Robust Gradient Estimation

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

Journal of The Royal Statistical Society Series B-statistical Methodology, (2020)

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Uniform Convergence of Rank-weighted Learning

Justin Khim, Liu Leqi,Adarsh Prasad,Pradeep Ravikumar

ICML, pp.5254-5263, (2020)

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On Completeness-aware Concept-Based Explanations in Deep Neural Networks

Chih-Kuan Yeh,Been Kim,Sercan Arik,Chun-Liang Li,Tomas Pfister,Pradeep Ravikumar

NIPS 2020, (2020)

Cited by8EIBibtex

On Learning Ising Models under Huber's Contamination Model

Adarsh Prasad, Vishwak Srinivasan,Sivaraman Balakrishnan,Pradeep Ravikumar

NIPS 2020, (2020)

EIBibtex

Generalized Boosting

Arun Suggala, Bingbin Liu,Pradeep Ravikumar

NIPS 2020, (2020)

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Minimizing FLOPs to Learn Efficient Sparse Representations

Biswajit Paria, Chih-Kuan Yeh,Ning Xu,Barnabas Poczos,Pradeep Ravikumar, Ian E.H. Yen

international conference on learning representations, (2020)

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Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification

Chen Dan, Yuting Wei,Pradeep Ravikumar

ICML, pp.2345-2355, (2020)

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

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

ICLR, (2020)

Cited by8EIBibtex

Learning Minimax Estimators via Online Learning

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

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Sharp Statistical Guaratees for Adversarially Robust Gaussian Classification

Chen Dan,Yuting Wei,Pradeep Ravikumar

ICML 2020, (2020)

Bibtex

Uniform Convergence of Rank-weighted Learning

Liu Leqi, Justin Khim,Adarsh Prasad,Pradeep Ravikumar

international conference on machine learning, (2020)

Bibtex

Automated Dependence Plots

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

UAI, pp.1238-1247, (2020)

EIBibtex

Class-Weighted Classification: Trade-offs and Robust Approaches

Xu Ziyu,Dan Chen, Khim Justin,Ravikumar Pradeep

ICML, pp.10544-10554, (2020)

EIBibtex

A Robust Univariate Mean Estimator is All You Need

Adarsh Prasad,Sivaraman Balakrishnan,Pradeep Ravikumar

AISTATS, pp.4034-4044, (2020)

EIBibtex

Minimizing FLOPs to Learn Efficient Sparse Representations

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

ICLR, (2020)

EIBibtex

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