Kevin Leyton-Brown

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Holger HoosRWTH Aachen University, Germany • Leiden University, Netherlands • University of British ColumbiaVerified email at cs.rwth-aachen.de
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
Jason HartfordSenior Machine Learning Research Scientist at Recursion PharmaVerified email at cs.ubc.ca
Moshe TennenholtzVerified email at ie.technion.ac.il
Milind TambeProfessor & Director CRCS Center @Harvard; Director "AI for Social Good" @Google ResearchVerified email at harvard.edu
David R. M. ThompsonGoogleVerified email at google.com
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Marius LindauerLeibniz University Hannover (Germany), Institute of Artificial Intelligence, L3S Research CenterVerified email at ai.uni-hannover.de
Thomas StützleF.R.S.-FNRS Research Director, Université Libre de Bruxelles (ULB)Verified email at ulb.ac.be
Neil NewmanUniversity of British ColumbiaVerified email at cs.ubc.ca
Alexandre FréchettePhD Student, University of British ColumbiaVerified email at cs.ubc.ca
Katharina EggenspergerResearcher, University of TübingenVerified email at uni-tuebingen.de
Ilya MironovMetaVerified email at meta.com
Anne CondonProfessor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
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, Computer Science, University of British Columbia; Canada CIFAR AI Chair

Verified email at cs.ubc.ca - Homepage

artificial intelligence machine learning game theory algorithms market design


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Multiagent systems: Algorithmic, game-theoretic, and logical foundations Y Shoham, K Leyton-Brown Cambridge University Press, 2009	3403	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	2735	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	1655	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	1172	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	1060	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	857	2001
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	795	2017
Essentials of Game Theory: A Concise Multidisciplinary Introduction K Leyton-Brown, Y Shoham Synthesis Lectures on Artificial Intelligence and Machine Learning, 1-88, 2008	730	2008
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	660	1999
Algorithm runtime prediction: Methods & evaluation F Hutter, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 206, 79-111, 2014	512	2014
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	501	2000
Artificial intelligence and life in 2030: the one hundred year study on artificial intelligence P Stone, R Brooks, E Brynjolfsson, R Calo, O Etzioni, G Hager, ... arXiv preprint arXiv:2211.06318, 2022	462	2022
An efficient approach for assessing hyperparameter importance F Hutter, H Hoos, K Leyton-Brown International Conference on Machine Learning, 2014	454	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	402	2013
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	261	2004
Deep IV: A flexible approach for counterfactual prediction J Hartford, G Lewis, K Leyton-Brown, M Taddy International Conference on Machine Learning, 1414-1423, 2017	257	2017
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	244	2004
Learning the empirical hardness of optimization problems: The case of combinatorial auctions K Leyton-Brown, E Nudelman, Y Shoham Principles and Practice of Constraint Programming-CP 2002: 8th International …, 2002	244	2002
A portfolio approach to algorithm selection K Leyton-Brown, E Nudelman, G Andrew, J McFadden, Y Shoham International Joint Conference on Artificial Intelligence (IJCAI) 1543, 2003, 2003	234	2003
Hydra: Automatically configuring algorithms for portfolio-based selection L Xu, H Hoos, K Leyton-Brown Proceedings of the AAAI Conference on Artificial Intelligence 24 (1), 210-216, 2010	228	2010

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