Kevin Leyton-Brown

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Holger HoosLeiden University, The Netherlands & University of British Columbia, CanadaVerified email at liacs.nl
Frank HutterProfessor of Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Yoav ShohamProfessor (emeritus)Verified email at cs.stanford.edu
Lin XuUniversity of British ColumbiaVerified email at cs.ubc.ca
Albert X. JiangAssistant Professor of Computer Science, Trinity UniversityVerified email at trinity.edu
James R. WrightUniversity of AlbertaVerified email at ualberta.ca
Moshe TennenholtzVerified email at ie.technion.ac.il
David R. M. ThompsonGoogleVerified email at google.com
Jason HartfordPhD Student, University of British ColumbiaVerified email at cs.ubc.ca
Milind TambeDirector CRCS Center @Harvard; Director "AI for Social Good" @Google India ResearchVerified email at harvard.edu
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Marius LindauerLeibniz University Hannover (Germany)Verified email at tnt.uni-hannover.de
Thomas StützleF.R.S.-FNRS Research Director, Université Libre de Bruxelles (ULB)Verified email at ulb.ac.be
Ilya MironovFacebook AIVerified email at fb.com
Alexandre FréchettePhD Student, University of British ColumbiaVerified email at cs.ubc.ca
Katharina EggenspergerPhD Student, Machine Learning Lab, University of FreiburgVerified email at informatik.uni-freiburg.de
Anne CondonProfessor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
Mark LillibridgeFacebookVerified email at cs.cmu.edu
Galen M AndrewGoogleVerified email at google.com
Tuomas SandholmAngel Jordan University Professor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu

Kevin Leyton-Brown

Professor of Computer Science, University of British Columbia; Canada CIFAR AI Chair, Amii

Verified email at cs.ubc.ca - Homepage

artificial intelligence machine learning game theory algorithms market design


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Multiagent systems: Algorithmic, game-theoretic, and logical foundations Y Shoham, K Leyton-Brown Cambridge University Press, 2009	2810	2009
Sequential model-based optimization for general algorithm configuration F Hutter, HH Hoos, K Leyton-Brown Proceedings of the 5th International Conference on Learning and Intelligent …, 2011	1763	2011
Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms C Thornton, F Hutter, HH Hoos, K Leyton-Brown Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013	1149	2013
ParamILS: an automatic algorithm configuration framework F Hutter, HH Hoos, K Leyton-Brown, T Stützle Journal of Artificial Intelligence Research (JAIR) 36 (1), 267-306, 2009	912	2009
SATzilla: Portfolio-based Algorithm Selection for SAT L Xu, F Hutter, HH Hoos, K Leyton-Brown Journal of Artificial Intelligence Research (JAIR) 32, 565-606, 2008	851	2008
Incentives for sharing in peer-to-peer networks P Golle, K Leyton-Brown, I Mironov, M Lillibridge ACM Conference on Electronic Commerce, 75-87, 2001	833	2001
Taming the computational complexity of combinatorial auctions: Optimal and approximate approaches Y Fujishima, K Leyton-Brown, Y Shoham International Joint Conference on Artificial Intelligence (IJCAI) 99, 548-553, 1999	657	1999
Essentials of Game Theory: A Concise Multidisciplinary Introduction K Leyton-Brown, Y Shoham Synthesis Lectures on Artificial Intelligence and Machine Learning, 1-88, 2008	576	2008
Towards a universal test suite for combinatorial auction algorithms K Leyton-Brown, M Pearson, Y Shoham Proceedings of the 2nd ACM conference on Electronic Commerce, 66-76, 2000	465	2000
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA L Kotthoff, C Thornton, HH Hoos, F Hutter, K Leyton-Brown Journal of Machine Learning Research 18 (25), 1--5, 2017	458	2017
Algorithm runtime prediction: Methods & evaluation F Hutter, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 206, 79-111, 2014	377	2014
Towards an empirical foundation for assessing Bayesian optimization of hyperparameters K Eggensperger, M Feurer, F Hutter, J Bergstra, J Snoek, H Hoos, ... NIPS Workshop on Bayesian Optimization in Theory and Practice, 2013	258	2013
Learning the empirical hardness of optimization problems: The case of combinatorial auctions K Leyton-Brown, E Nudelman, Y Shoham International conference on principles and practice of constraint …, 2002	227	2002
Artificial intelligence and life in 2030. One hundred year study on artificial intelligence: Report of the 2015-2016 Study Panel P Stone, R Brooks, E Brynjolfsson, R Calo, O Etzioni, G Hager, ... Stanford University. http://ai100.stanford.edu/2016-report., 2016	225*	2016
Understanding random SAT: Beyond the clauses-to-variables ratio E Nudelman, K Leyton-Brown, H Hoos, A Devkar, Y Shoham Principles and Practice of Constraint Programming, 438-452, 2004	225	2004
An efficient approach for assessing hyperparameter importance F Hutter, H Hoos, K Leyton-Brown International Conference on Machine Learning, 2014	224	2014
Run the GAMUT: A comprehensive approach to evaluating game-theoretic algorithms E Nudelman, J Wortman, Y Shoham, K Leyton-Brown Proceedings of the Third International Joint Conference on Autonomous Agents …, 2004	212	2004
Deep optimization for spectrum repacking N Newman, A Fréchette, K Leyton-Brown Communications of the ACM 61 (1), 97-104, 2017	196*	2017
An algorithm for multi-unit combinatorial auctions K Leyton-Brown, Y Shoham, M Tennenholtz National Conference on Artificial Intelligence (AAAI), 56-61, 2000	195	2000
Performance prediction and automated tuning of randomized and parametric algorithms F Hutter, Y Hamadi, HH Hoos, K Leyton-Brown Principles and Practice of Constraint Programming, 213-228, 2006	193	2006

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