Jacob Abernethy

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	All	Since 2016
Citations	2744	1568
h-index	26	22
i10-index	49	42

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2007200820092010201120122013201420152016201720182019202020219 26 59 111 149 182 192 224 197 233 246 279 304 435 62

Co-authors

Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Theodoros EvgeniouINSEADVerified email at insead.edu
Jean-Philippe VertGoogle Brain / Mines ParisTechVerified email at mines-paristech.fr
Ambuj Tewari | अम्बुज तिवारीAssociate Professor, Department of Statistics and Department of EECS, University of MichiganVerified email at umich.edu
Elad HazanProfessor at Princeton University and Director Google AI PrincetonVerified email at cs.princeton.edu
Rafael FrongilloComputer Science, CU BoulderVerified email at cs.berkeley.edu
Olivier ChapelleGoogleVerified email at chapelle.cc
Carlos CastilloDistinguished Research Professor, Universitat Pompeu FabraVerified email at upf.edu
Jennifer Wortman VaughanSenior Principal Researcher, Microsoft Research, New York CityVerified email at microsoft.com
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
Yiling ChenHarvard UniversityVerified email at seas.harvard.edu
John LangfordMicrosoft Research New YorkVerified email at hunch.net
Alekh AgarwalMicrosoft ResearchVerified email at microsoft.com
Chien-Ju HoWashington University in St. LouisVerified email at wustl.edu
niv buchbinderTel Aviv universityVerified email at post.tau.ac.il
Isabelle StantonSoftware Engineer at GoogleVerified email at eecs.berkeley.edu
Satyen KaleStaff Research Scientist, Google ResearchVerified email at google.com
Michael KearnsProfessor of Computer Science, University of PennsylvaniaVerified email at cis.upenn.edu
Qingsi WangGoogleVerified email at google.com
Shie MannorProfessor of Electrical Engineering @ Technion & Researcher @ Nvidia ResearchVerified email at technion.ac.il

Jacob Abernethy

Assistant Professor, University of Michigan

Verified email at umich.edu

Machine Learning Game Theory Sequential Decision Making


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Competing in the dark: An efficient algorithm for bandit linear optimization JD Abernethy, E Hazan, A Rakhlin	290	2009
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	278	2009
On convergence and stability of gans N Kodali, J Abernethy, J Hays, Z Kira arXiv preprint arXiv:1705.07215, 2017	263*	2017
Optimal strategies and minimax lower bounds for online convex games J Abernethy, PL Bartlett, A Rakhlin, A Tewari	147	2008
Optimal strategies and minimax lower bounds for online convex games J Abernethy, PL Bartlett, A Rakhlin, A Tewari	147	2008
Low-rank matrix factorization with attributes J Abernethy, F Bach, T Evgeniou, JP Vert arXiv preprint cs/0611124, 2006	103	2006
Web spam identification through content and hyperlinks J Abernethy, O Chapelle, C Castillo Proceedings of the 4th international workshop on Adversarial information …, 2008	102	2008
A stochastic view of optimal regret through minimax duality J Abernethy, A Agarwal, PL Bartlett, A Rakhlin arXiv preprint arXiv:0903.5328, 2009	99	2009
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	82	2013
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	77	2011
Graph regularization methods for web spam detection J Abernethy, O Chapelle, C Castillo Machine Learning 81 (2), 207-225, 2010	76	2010
A collaborative mechanism for crowdsourcing prediction problems J Abernethy, RM Frongillo arXiv preprint arXiv:1111.2664, 2011	66	2011
Multitask learning with expert advice J Abernethy, P Bartlett, A Rakhlin International Conference on Computational Learning Theory, 484-498, 2007	64	2007
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	58	2007
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	53	2012
An optimization-based framework for automated market-making J Abernethy, Y Chen, J Wortman Vaughan Proceedings of the 12th ACM conference on Electronic commerce, 297-306, 2011	49	2011
WITCH: A new approach to Web spam detection J Abernethy, O Chapelle, C Castillo In Proceedings of the 4th International Workshop on Adversarial Information …, 2008	49	2008
Online linear optimization via smoothing J Abernethy, C Lee, A Sinha, A Tewari Conference on Learning Theory, 807-823, 2014	47	2014
Beating the adaptive bandit with high probability J Abernethy, A Rakhlin 2009 Information Theory and Applications Workshop, 280-289, 2009	47	2009
A characterization of scoring rules for linear properties JD Abernethy, RM Frongillo Conference on Learning Theory, 27.1-27.13, 2012	45	2012

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