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One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning


Mar 04, 2021
Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao


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Robust learning under clean-label attack


Mar 03, 2021
Avrim Blum, Steve Hanneke, Jian Qian, Han Shao


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Communication-Aware Collaborative Learning


Dec 19, 2020
Avrim Blum, Shelby Heinecke, Lev Reyzin


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Online Learning with Primary and Secondary Losses


Oct 27, 2020
Avrim Blum, Han Shao


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On the Power of Abstention and Data-Driven Decision Making for Adversarial Robustness


Oct 13, 2020
Maria-Florina Balcan, Avrim Blum, Dravyansh Sharma, Hongyang Zhang

* 31 pages, 9 figures 

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Active Local Learning


Sep 04, 2020
Arturs Backurs, Avrim Blum, Neha Gupta

* Published at COLT 2020 

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The Strategic Perceptron


Aug 04, 2020
Saba Ahmadi, Hedyeh Beyhaghi, Avrim Blum, Keziah Naggita


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Learning Complexity of Simulated Annealing


Mar 06, 2020
Avrim Blum, Chen Dan, Saeed Seddighin

* 45 pages 

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Random Smoothing Might be Unable to Certify $\ell_\infty$ Robustness for High-Dimensional Images


Mar 05, 2020
Avrim Blum, Travis Dick, Naren Manoj, Hongyang Zhang

* 20 pages, 2 figures; Code is available at https://github.com/hongyanz/TRADES-smoothing 

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Recovering from Biased Data: Can Fairness Constraints Improve Accuracy?


Dec 02, 2019
Avrim Blum, Kevin Stangl


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Advancing subgroup fairness via sleeping experts


Sep 18, 2019
Avrim Blum, Thodoris Lykouris


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On preserving non-discrimination when combining expert advice


Oct 28, 2018
Avrim Blum, Suriya Gunasekar, Thodoris Lykouris, Nathan Srebro

* To appear in NIPS 2018 

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Active Tolerant Testing


Nov 01, 2017
Avrim Blum, Lunjia Hu


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Lifelong Learning in Costly Feature Spaces


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


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Sparse Approximation via Generating Point Sets


Jun 29, 2017
Avrim Blum, Sariel Har-Peled, Benjamin Raichel


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Efficient PAC Learning from the Crowd


Apr 13, 2017
Pranjal Awasthi, Avrim Blum, Nika Haghtalab, Yishay Mansour


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Generalized Topic Modeling


Nov 04, 2016
Avrim Blum, Nika Haghtalab


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The Ladder: A Reliable Leaderboard for Machine Learning Competitions


Feb 16, 2015
Avrim Blum, Moritz Hardt


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Efficient Representations for Life-Long Learning and Autoencoding


Dec 04, 2014
Maria-Florina Balcan, Avrim Blum, Santosh Vempala


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Learning Mixtures of Ranking Models


Oct 31, 2014
Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan


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Active Learning and Best-Response Dynamics


Jun 25, 2014
Maria-Florina Balcan, Chris Berlind, Avrim Blum, Emma Cohen, Kaushik Patnaik, Le Song


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Distributed Learning, Communication Complexity and Privacy


May 25, 2012
Maria-Florina Balcan, Avrim Blum, Shai Fine, Yishay Mansour

* 19 pages 

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Fast Private Data Release Algorithms for Sparse Queries


Nov 29, 2011
Avrim Blum, Aaron Roth


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A Learning Theory Approach to Non-Interactive Database Privacy


Sep 10, 2011
Avrim Blum, Katrina Ligett, Aaron Roth

* Full Version. Extended Abstract appeared in STOC 2008 

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Separating populations with wide data: A spectral analysis


Jan 29, 2009
Avrim Blum, Amin Coja-Oghlan, Alan Frieze, Shuheng Zhou

* Electronic Journal of Statistics 2009, Vol. 3, 76-113 
* Published in at http://dx.doi.org/10.1214/08-EJS289 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org

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Noise-Tolerant Learning, the Parity Problem, and the Statistical Query Model


Oct 15, 2000
Avrim Blum, Adam Kalai, Hal Wasserman


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