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Jacob Abernethy
Jacob Abernethy
Assistant Professor, University of Michigan
Verifierad e-postadress på umich.edu
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On convergence and stability of gans
N Kodali, J Abernethy, J Hays, Z Kira
arXiv preprint arXiv:1705.07215, 2017
659*2017
Competing in the dark: An efficient algorithm for bandit linear optimization
JD Abernethy, E Hazan, A Rakhlin
3812009
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization.
J Abernethy, F Bach, T Evgeniou, JP Vert
Journal of Machine Learning Research 10 (3), 2009
3012009
Optimal strategies and minimax lower bounds for online convex games
J Abernethy, PL Bartlett, A Rakhlin, A Tewari
1762008
Optimal strategies and minimax lower bounds for online convex games
J Abernethy, PL Bartlett, A Rakhlin, A Tewari
1762008
Dynamic online pricing with incomplete information using multiarmed bandit experiments
K Misra, EM Schwartz, J Abernethy
Marketing Science 38 (2), 226-252, 2019
1502019
Blackwell approachability and no-regret learning are equivalent
J Abernethy, PL Bartlett, E Hazan
Proceedings of the 24th Annual Conference on Learning Theory, 27-46, 2011
1182011
Low-rank matrix factorization with attributes
J Abernethy, F Bach, T Evgeniou, JP Vert
arXiv preprint cs/0611124, 2006
1082006
Web spam identification through content and hyperlinks
J Abernethy, O Chapelle, C Castillo
Proceedings of the 4th international workshop on Adversarial information …, 2008
1062008
A stochastic view of optimal regret through minimax duality
J Abernethy, A Agarwal, PL Bartlett, A Rakhlin
arXiv preprint arXiv:0903.5328, 2009
1012009
Efficient market making via convex optimization, and a connection to online learning
J Abernethy, Y Chen, JW Vaughan
ACM Transactions on Economics and Computation (TEAC) 1 (2), 1-39, 2013
962013
Graph regularization methods for web spam detection
J Abernethy, O Chapelle, C Castillo
Machine Learning 81, 207-225, 2010
832010
A collaborative mechanism for crowdsourcing prediction problems
JD Abernethy, R Frongillo
Advances in neural information processing systems 24, 2011
752011
Eliciting consumer preferences using robust adaptive choice questionnaires
J Abernethy, T Evgeniou, O Toubia, JP Vert
IEEE Transactions on Knowledge and Data Engineering 20 (2), 145-155, 2007
732007
Interior-point methods for full-information and bandit online learning
JD Abernethy, E Hazan, A Rakhlin
IEEE Transactions on Information Theory 58 (7), 4164-4175, 2012
682012
Online linear optimization via smoothing
J Abernethy, C Lee, A Sinha, A Tewari
Conference on Learning Theory, 807-823, 2014
672014
Beating the adaptive bandit with high probability
J Abernethy, A Rakhlin
2009 Information Theory and Applications Workshop, 280-289, 2009
652009
Fighting bandits with a new kind of smoothness
JD Abernethy, C Lee, A Tewari
Advances in Neural Information Processing Systems 28, 2015
632015
Multitask learning with expert advice
J Abernethy, P Bartlett, A Rakhlin
Learning Theory: 20th Annual Conference on Learning Theory, COLT 2007, San …, 2007
632007
Last-iterate convergence rates for min-max optimization
J Abernethy, KA Lai, A Wibisono
arXiv preprint arXiv:1906.02027, 2019
622019
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Artiklar 1–20