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Towards optimally abstaining from prediction


May 28, 2021
Adam Tauman Kalai, Varun Kanade

* 23 pages 

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Efficient Learning with Arbitrary Covariate Shift


Feb 15, 2021
Adam Kalai, Varun Kanade


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Lottery Tickets in Linear Models: An Analysis of Iterative Magnitude Pruning


Aug 06, 2020
Bryn Elesedy, Varun Kanade, Yee Whye Teh

* 16 pages, 1 figure. Corrections to previous version 

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How benign is benign overfitting?


Jul 08, 2020
Amartya Sanyal, Puneet K Dokania, Varun Kanade, Philip H. S. Torr


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Differentiable Causal Backdoor Discovery


Mar 03, 2020
Limor Gultchin, Matt J. Kusner, Varun Kanade, Ricardo Silva

* Published in the Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS) 2020, Palermo, Italy 

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The Statistical Complexity of Early Stopped Mirror Descent


Feb 01, 2020
Tomas Vaškevičius, Varun Kanade, Patrick Rebeschini


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Online k-means Clustering


Sep 15, 2019
Vincent Cohen-Addad, Benjamin Guedj, Varun Kanade, Guy Rom

* 11 pages, 1 figure 

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On the Hardness of Robust Classification


Sep 12, 2019
Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell

* To appear in the proceedings of Neural Information Processing Systems Conference (2019) 

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Implicit Regularization for Optimal Sparse Recovery


Sep 11, 2019
Tomas Vaškevičius, Varun Kanade, Patrick Rebeschini

* To appear in NeurIPS 2019 

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Adaptive Reduced Rank Regression


May 28, 2019
Qiong Wu, Felix Ming Fai Wong, Zhenming Liu, Yanhua Li, Varun Kanade

* 27 pages 

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Decentralized Cooperative Stochastic Multi-armed Bandits


Oct 10, 2018
David Martínez-Rubio, Varun Kanade, Patrick Rebeschini


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Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain


Aug 06, 2018
Quentin Berthet, Varun Kanade


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Intriguing Properties of Learned Representations


Jun 11, 2018
Amartya Sanyal, Varun Kanade, Philip H. S. Torr


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TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service


Jun 09, 2018
Amartya Sanyal, Matt J. Kusner, Adrià Gascón, Varun Kanade

* Accepted at International Conference in Machine Learning (ICML), 2018 

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Learning DNFs under product distributions via μ-biased quantum Fourier sampling


Mar 06, 2018
Varun Kanade, Andrea Rocchetto, Simone Severini

* 17 pages; v2 minor corrections and clarifications 

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From which world is your graph?


Nov 03, 2017
Cheng Li, Felix Wong, Zhenming Liu, Varun Kanade

* To appear in NIPS 2017 

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Hierarchical Clustering: Objective Functions and Algorithms


Apr 07, 2017
Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn, Claire Mathieu


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Reliably Learning the ReLU in Polynomial Time


Nov 30, 2016
Surbhi Goel, Varun Kanade, Adam Klivans, Justin Thaler


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Online Optimization of Smoothed Piecewise Constant Functions


May 20, 2016
Vincent Cohen-Addad, Varun Kanade


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MCMC Learning


Jun 12, 2015
Varun Kanade, Elchanan Mossel

* 28 pages, 1 figure 

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Learning with a Drifting Target Concept


May 20, 2015
Steve Hanneke, Varun Kanade, Liu Yang


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Attribute-Efficient Evolvability of Linear Functions


Apr 03, 2014
Elaine Angelino, Varun Kanade


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Distribution-Independent Reliable Learning


Feb 20, 2014
Varun Kanade, Justin Thaler

* 20 pages 

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Learning using Local Membership Queries


Apr 17, 2013
Pranjal Awasthi, Vitaly Feldman, Varun Kanade


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Distributed Non-Stochastic Experts


Nov 14, 2012
Varun Kanade, Zhenming Liu, Bozidar Radunovic


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Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression


Apr 11, 2011
Sham Kakade, Adam Tauman Kalai, Varun Kanade, Ohad Shamir


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Evolution with Drifting Targets


May 19, 2010
Varun Kanade, Leslie G. Valiant, Jennifer Wortman Vaughan


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