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 HartfordPost-doc, MILAVerified email at cs.ubc.ca
David R. M. ThompsonGoogleVerified email at google.com
Moshe TennenholtzVerified email at ie.technion.ac.il
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Milind TambeDirector CRCS Center @Harvard; Director "AI for Social Good" @Google India ResearchVerified email at harvard.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
Alexandre FréchettePhD Student, University of British ColumbiaVerified email at cs.ubc.ca
Neil NewmanUniversity 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
Galen M AndrewGoogleVerified email at google.com
Ilya MironovMeta AIVerified email at fb.com
Mark LillibridgeFacebookVerified 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


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	3137	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	2295	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	1395	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	1076	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	971	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	841	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	659	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	654	1999
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	639	2017
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	485	2000
Algorithm runtime prediction: Methods & evaluation F Hutter, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 206, 79-111, 2014	457	2014
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, ... Stanford University, 2016	355	2016
An efficient approach for assessing hyperparameter importance F Hutter, H Hoos, K Leyton-Brown International Conference on Machine Learning, 2014	340	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	332	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	240	2004
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	234	2002
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	230	2004
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	218	2003
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	212	2006
Deep optimization for spectrum repacking N Newman, A Fréchette, K Leyton-Brown Communications of the ACM 61 (1), 97-104, 2017	210*	2017

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