Holger Hoos

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Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI ChairVerified email at cs.ubc.ca
Thomas StützleF.R.S.-FNRS Research Director, Université Libre de Bruxelles (ULB)Verified email at ulb.ac.be
Frank HutterProfessor of Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Lin XuUniversity of British ColumbiaVerified email at cs.ubc.ca
Craig BoutilierPrincipal Scientist, GoogleVerified email at google.com
Anne CondonProfessor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
Dave A. D. TompkinsLecturer, Computer Science, University of WaterlooVerified email at uwaterloo.ca
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Chris FawcettPhD Student, University of British ColumbiaVerified email at cs.ubc.ca
Marius LindauerLeibniz University Hannover (Germany), Institute of Artificial Intelligence LUH|AI, L3S ResearchVerified email at ai.uni-hannover.de
Ronen BrafmanDepartment of Computer Science, Ben-Gurion UniversityVerified email at cs.bgu.ac.il
Nima AghaeepourStanford UniversityVerified email at stanford.edu
David PooleProfessor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
Ryan BrinkmanBritish Columbia Cancer AgencyVerified email at bccrc.ca
Carmel DomshlakProfessor, TechnionVerified email at ie.technion.ac.il
Torsten SchaubUniversity of PotsdamVerified email at cs.uni-potsdam.de
Sam BaylessUniversity of British Columbia, Amazon Web ServicesVerified email at cs.ubc.ca
Jesper van EngelenAutonomous Vehicles at NVIDIA, previously Leiden University and ETH ZürichVerified email at liacs.nl
Jürgen KilianKilian IT-Consulting, Darmstadt University of TechnologyVerified email at noteserver.org
Katharina EggenspergerEarly Career Group Leader "AutoML for Science" | University of TübingenVerified email at uni-tuebingen.de

Holger Hoos

RWTH Aachen University, Germany • Leiden University, Netherlands • University of British Columbia

Verified email at cs.rwth-aachen.de - Homepage

Artificial Intelligence Machine Learning Automated Reasoning Empirical Algorithmics Automated Algorithm Design


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MAX–MIN ant system T Stützle, HH Hoos Future generation computer systems 16 (8), 889-914, 2000	4435	2000
Sequential model-based optimization for general algorithm configuration F Hutter, HH Hoos, K Leyton-Brown Learning and Intelligent Optimization: 5th International Conference, LION 5 …, 2011	2854	2011
Stochastic local search: Foundations and applications HH Hoos, T Stützle Elsevier, 2004	2374	2004
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	1832	2013
A survey on semi-supervised learning JE Van Engelen, HH Hoos Machine learning 109 (2), 373-440, 2020	1701	2020
MAX-MIN ant system and local search for the traveling salesman problem T Stutzle, H Hoos IEEE International Conference on Evolutionary Computation 1997, 309-314, 1997	1437	1997
CP-nets: A tool for representing and reasoning withconditional ceteris paribus preference statements C Boutilier, RI Brafman, C Domshlak, HH Hoos, D Poole Journal of artificial intelligence research 21, 135-191, 2004	1230	2004
ParamILS: an automatic algorithm configuration framework F Hutter, HH Hoos, K Leyton-Brown, T Stützle Journal of artificial intelligence research 36, 267-306, 2009	1199	2009
SATzilla: portfolio-based algorithm selection for SAT L Xu, F Hutter, HH Hoos, K Leyton-Brown Journal of artificial intelligence research 32, 565-606, 2008	1087	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, 1-5, 2017	840	2017
Critical assessment of automated flow cytometry data analysis techniques N Aghaeepour, G Finak, FlowCAP Consortium, Dream Consortium, ... Nature methods 10 (3), 228-238, 2013	630	2013
Algorithm runtime prediction: Methods & evaluation F Hutter, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 206, 79-111, 2014	528	2014
Improvements on the Ant-System: Introducing the MAX-MIN Ant System GD Smith, NC Steele, RF Albrecht, T Stützle, H Hoos Artificial Neural Nets and Genetic Algorithms: Proceedings of the …, 1998	507	1998
An efficient approach for assessing hyperparameter importance F Hutter, H Hoos, K Leyton-Brown	491	2014
SATLIB: An online resource for research on SAT HH Hoos, T Stützle Sat 2000, 283-292, 2000	466	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 10 (3), 2013	425	2013
Automatic algorithm configuration based on local search F Hutter, HH Hoos, T Stützle Aaai 7, 1152-1157, 2007	395	2007
An ant colony optimisation algorithm for the 2D and 3D hydrophobic polar protein folding problem A Shmygelska, HH Hoos BMC bioinformatics 6, 1-22, 2005	374	2005
Automated algorithm selection: Survey and perspectives P Kerschke, HH Hoos, F Neumann, H Trautmann Evolutionary computation 27 (1), 3-45, 2019	369	2019
Reasoning With Conditional Ceteris Paribus Preference Statements. C Boutilier, RI Brafman, HH Hoos, D Poole UAI 99, 71-80, 1999	367	1999

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