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 HutterELLIS Institute & Professor, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Yoav ShohamProfessor (emeritus)Verified email at cs.stanford.edu
Lin XuNETINT, University 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 HartfordStaff Machine Learning Research Scientist at Valence Labs / Recursion PharmaVerified email at cs.ubc.ca
Milind TambeProfessor & Director CRCS Center @Harvard; Director "AI for Social Good" @Google ResearchVerified email at harvard.edu
Moshe TennenholtzVerified email at ie.technion.ac.il
Yoav LevineStanford UniversityVerified email at mail.huji.ac.il
David R. M. ThompsonGoogleVerified email at google.com
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Ece KamarMicrosoft ResearchVerified email at microsoft.com
Ryan CaloUniversity of WashingtonVerified email at uw.edu
rodney brooksProfessor of Computer Science, MITVerified email at csail.mit.edu
David C. ParkesGeorge F. Colony Professor of Computer Science, Harvard UniversityVerified email at eecs.harvard.edu
Oren EtzioniProfessor, University of WashingtonVerified email at cs.uw.edu
Julia HirschbergColumbia UniversityVerified email at cs.columbia.edu
Marius LindauerLeibniz University Hannover (Germany), Institute of Artificial Intelligence LUH|AI, L3S ResearchVerified email at ai.uni-hannover.de
Neil NewmanUniversity of British ColumbiaVerified email at cs.ubc.ca

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	3661	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	3191	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	1996	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	1255	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	1138	2008
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, 2016	1124*	2016
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	944	2017
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	868	2001
Essentials of Game Theory: A Concise Multidisciplinary Introduction K Leyton-Brown, Y Shoham Synthesis Lectures on Artificial Intelligence and Machine Learning, 1-88, 2008	804*	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	683	1999
An efficient approach for assessing hyperparameter importance F Hutter, H Hoos, K Leyton-Brown International Conference on Machine Learning, 2014	583	2014
Algorithm runtime prediction: Methods & evaluation F Hutter, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 206, 79-111, 2014	560	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	525	2000
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	457	2013
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	341	2017
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	277	2004
ASlib: A benchmark library for algorithm selection B Bischl, P Kerschke, L Kotthoff, M Lindauer, Y Malitsky, A Fréchette, ... Artificial Intelligence 237, 41–58, 2014	275	2014
Automated configuration of mixed integer programming solvers F Hutter, HH Hoos, K Leyton-Brown Integration of AI and OR Techniques in Constraint Programming for …, 2010	254	2010
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	253	2002
In-context retrieval-augmented language models O Ram, Y Levine, I Dalmedigos, D Muhlgay, A Shashua, K Leyton-Brown, ... Transactions of the Association for Computational Linguistics 11, 1316-1331, 2023	251	2023

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