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A Theory of PAC Learnability of Partial Concept Classes


Jul 20, 2021
Noga Alon, Steve Hanneke, Ron Holzman, Shay Moran


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Open Problem: Is There an Online Learning Algorithm That Learns Whenever Online Learning Is Possible?


Jul 20, 2021
Steve Hanneke


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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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Adversarially Robust Learning with Unknown Perturbation Sets


Feb 03, 2021
Omar Montasser, Steve Hanneke, Nathan Srebro


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Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games


Feb 02, 2021
Steve Hanneke, Roi Livni, Shay Moran


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Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound


Nov 09, 2020
Steve Hanneke, Aryeh Kontorovich


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A Theory of Universal Learning


Nov 09, 2020
Olivier Bousquet, Steve Hanneke, Shay Moran, Ramon van Handel, Amir Yehudayoff


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Reducing Adversarially Robust Learning to Non-Robust PAC Learning


Oct 22, 2020
Omar Montasser, Steve Hanneke, Nathan Srebro

* To appear in NeurIPS 2020 

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A No-Free-Lunch Theorem for MultiTask Learning


Jul 13, 2020
Steve Hanneke, Samory Kpotufe


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Proper Learning, Helly Number, and an Optimal SVM Bound


May 24, 2020
Olivier Bousquet, Steve Hanneke, Shay Moran, Nikita Zhivotovskiy


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On the Value of Target Data in Transfer Learning


Feb 12, 2020
Steve Hanneke, Samory Kpotufe

* NeurIPS 2019 

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Universal Bayes consistency in metric spaces


Jun 26, 2019
Steve Hanneke, Aryeh Kontorovich, Sivan Sabato, Roi Weiss

* arXiv admin note: text overlap with arXiv:1705.08184 

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VC Classes are Adversarially Robustly Learnable, but Only Improperly


Feb 12, 2019
Omar Montasser, Steve Hanneke, Nathan Srebro


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Agnostic Sample Compression for Linear Regression


Oct 03, 2018
Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi


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Sample Compression for Real-Valued Learners


May 21, 2018
Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi


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A New Lower Bound for Agnostic Learning with Sample Compression Schemes


May 21, 2018
Steve Hanneke, Aryeh Kontorovich


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Testing Piecewise Functions


May 20, 2018
Steve Hanneke, Liu Yang


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Statistical Learning under Nonstationary Mixing Processes


May 20, 2018
Steve Hanneke, Liu Yang


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Actively Avoiding Nonsense in Generative Models


Feb 20, 2018
Steve Hanneke, Adam Kalai, Gautam Kamath, Christos Tzamos


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Learning Whenever Learning is Possible: Universal Learning under General Stochastic Processes


Jun 05, 2017
Steve Hanneke


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Learning with Changing Features


Apr 29, 2017
Amit Dhurandhar, Steve Hanneke, Liu Yang


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Refined Error Bounds for Several Learning Algorithms


Sep 10, 2016
Steve Hanneke

* Journal of Machine Learning Research, Vol. 17 (2016), No. 135, pp. 1-55 

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The Optimal Sample Complexity of PAC Learning


Feb 07, 2016
Steve Hanneke

* Journal of Machine Learning Research, Vol. 17 (2016), No. 38, pp. 1-15 

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Bounds on the Minimax Rate for Estimating a Prior over a VC Class from Independent Learning Tasks


May 20, 2015
Liu Yang, Steve Hanneke, Jaime Carbonell


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Learning with a Drifting Target Concept


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


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Surrogate Losses in Passive and Active Learning


Mar 14, 2015
Steve Hanneke, Liu Yang


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Minimax Analysis of Active Learning


Oct 03, 2014
Steve Hanneke, Liu Yang


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A Compression Technique for Analyzing Disagreement-Based Active Learning


Apr 05, 2014
Yair Wiener, Steve Hanneke, Ran El-Yaniv


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