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A Learning Theoretic Perspective on Local Explainability


Nov 02, 2020
Jeffrey Li, Vaishnavh Nagarajan, Gregory Plumb, Ameet Talwalkar


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Understanding the Failure Modes of Out-of-Distribution Generalization


Oct 29, 2020
Vaishnavh Nagarajan, Anders Andreassen, Behnam Neyshabur


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Provably Safe PAC-MDP Exploration Using Analogies


Jul 07, 2020
Melrose Roderick, Vaishnavh Nagarajan, J. Zico Kolter

* 9 pages, 3 figures 

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Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience


May 30, 2019
Vaishnavh Nagarajan, J. Zico Kolter

* Published as a conference paper at ICLR 2019 

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Uniform convergence may be unable to explain generalization in deep learning


Apr 02, 2019
Vaishnavh Nagarajan, J. Zico Kolter


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Generalization in Deep Networks: The Role of Distance from Initialization


Jan 13, 2019
Vaishnavh Nagarajan, J. Zico Kolter

* Spotlight paper at NeurIPS 2017 workshop on Deep Learning: Bridging Theory and Practice 

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Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems


Oct 16, 2018
Maria-Florina Balcan, Vaishnavh Nagarajan, Ellen Vitercik, Colin White


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On Adversarial Risk and Training


Jun 11, 2018
Arun Sai Suggala, Adarsh Prasad, Vaishnavh Nagarajan, Pradeep Ravikumar


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Gradient descent GAN optimization is locally stable


Jan 13, 2018
Vaishnavh Nagarajan, J. Zico Kolter


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Lifelong Learning in Costly Feature Spaces


Jun 30, 2017
Maria-Florina Balcan, Avrim Blum, Vaishnavh Nagarajan


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A Reinforcement Learning Approach to Online Learning of Decision Trees


Jul 24, 2015
Abhinav Garlapati, Aditi Raghunathan, Vaishnavh Nagarajan, Balaraman Ravindran


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