Kevin Leyton-Brown

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Holger HoosRWTH Aachen University, Germany • Leiden University, Netherlands • University of British ColumbiaEmail verificata su cs.rwth-aachen.de
Frank HutterELLIS Institute & Professor, University of Freiburg, GermanyEmail verificata su cs.uni-freiburg.de
Yoav ShohamProfessor (emeritus)Email verificata su cs.stanford.edu
Lin XuNETINT, University of British ColumbiaEmail verificata su cs.ubc.ca
James R. WrightUniversity of AlbertaEmail verificata su ualberta.ca
Jason HartfordDame Kathleen Ollerenshaw Fellow, University of Manchester; Research Scientist at Valence LabsEmail verificata su cs.ubc.ca
Milind TambeProfessor & Director CRCS Center @Harvard; Director "AI for Social Good" @Google ResearchEmail verificata su harvard.edu
Yoav LevineAA-I TechnologiesEmail verificata su doubleai.com
Moshe TennenholtzEmail verificata su ie.technion.ac.il
David R. M. ThompsonGoogleEmail verificata su google.com
Lars KotthoffUniversity of WyomingEmail verificata su uwyo.edu
Ece KamarMicrosoft ResearchEmail verificata su microsoft.com
Ryan CaloUniversity of WashingtonEmail verificata su uw.edu
rodney brooksProfessor of Computer Science, MITEmail verificata su csail.mit.edu
David C. ParkesGeorge F. Colony Professor of Computer Science, Harvard UniversityEmail verificata su eecs.harvard.edu
Oren EtzioniProfessor, University of WashingtonEmail verificata su cs.uw.edu
Julia HirschbergColumbia UniversityEmail verificata su cs.columbia.edu
Amnon ShashuaProfessor of Computer Science, the Hebrew University of JerusalemEmail verificata su cs.huji.ac.il
Neil NewmanUniversity of British ColumbiaEmail verificata su cs.ubc.ca
Erik BrynjolfssonProfessor at Stanford; NBER; Stanford Digital Economy LabEmail verificata su stanford.edu

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Kevin Leyton-Brown

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

Email verificata su cs.ubc.ca - Home page

artificial intelligence machine learning game theory algorithms market design


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Multiagent systems: Algorithmic, game-theoretic, and logical foundations Y Shoham, K Leyton-Brown Cambridge University Press, 2009	3787	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	3362	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	2105	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	1283	2009
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	1250*	2016
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	1175	2008
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	985	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	872	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	852*	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	684	1999
An efficient approach for assessing hyperparameter importance F Hutter, H Hoos, K Leyton-Brown International Conference on Machine Learning, 2014	636	2014
Algorithm runtime prediction: Methods & evaluation F Hutter, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 206, 79-111, 2014	584	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	527	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	470	2013
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	391	2023
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	372	2017
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	289	2014
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	285	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	257	2002
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	256	2010

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