Kevin Leyton-Brown
Kevin Leyton-Brown
Professor, Computer Science, University of British Columbia; Canada CIFAR AI Chair
Bestätigte E-Mail-Adresse bei cs.ubc.ca - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Multiagent systems: Algorithmic, game-theoretic, and logical foundations
Y Shoham, K Leyton-Brown
Cambridge University Press, 2009
28362009
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
17892011
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
11692013
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
9192009
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
8582008
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
8332001
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
6591999
Essentials of Game Theory: A Concise Multidisciplinary Introduction
K Leyton-Brown, Y Shoham
Synthesis Lectures on Artificial Intelligence and Machine Learning, 1-88, 2008
5852008
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
4702017
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
4662000
Algorithm runtime prediction: Methods & evaluation
F Hutter, L Xu, HH Hoos, K Leyton-Brown
Artificial Intelligence 206, 79-111, 2014
3822014
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
2642013
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
234*2016
An efficient approach for assessing hyperparameter importance
F Hutter, H Hoos, K Leyton-Brown
International Conference on Machine Learning, 2014
2302014
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
2282002
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
2272004
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
2122004
Deep optimization for spectrum repacking
N Newman, A Fréchette, K Leyton-Brown
Communications of the ACM 61 (1), 97-104, 2017
197*2017
An algorithm for multi-unit combinatorial auctions
K Leyton-Brown, Y Shoham, M Tennenholtz
National Conference on Artificial Intelligence (AAAI), 56-61, 2000
1962000
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
1952006
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