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, L3S Research CenterVerified email at ai.uni-hannover.de
Ronen BrafmanDepartment of Computer Science, Ben-Gurion UniversityVerified email at cs.bgu.ac.il
David PooleProfessor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
Nima AghaeepourStanford UniversityVerified email at stanford.edu
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
Heike TrautmannProfessor of Data Science: Statistics and Optimization, Department of Information SystemsVerified email at wi.uni-muenster.de
Katharina EggenspergerResearcher, University of TübingenVerified email at uni-tuebingen.de
Alan J. HuProfessor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca

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


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
MAX–MIN ant system T Stützle, HH Hoos Future generation computer systems 16 (8), 889-914, 2000	4398	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	2732	2011
Stochastic local search: Foundations and applications HH Hoos, T Stützle Elsevier, 2004	2338	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	1743	2013
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	1424	1997
A survey on semi-supervised learning JE Van Engelen, HH Hoos Machine learning 109 (2), 373-440, 2020	1394	2020
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	1208	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	1178	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	1060	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	791	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	621	2013
Algorithm runtime prediction: Methods & evaluation F Hutter, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 206, 79-111, 2014	512	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	499	1998
An efficient approach for assessing hyperparameter importance F Hutter, H Hoos, K Leyton-Brown	452	2014
SATLIB: An online resource for research on SAT HH Hoos, T Stützle Sat 2000, 283-292, 2000	452	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	401	2013
Automatic algorithm configuration based on local search F Hutter, HH Hoos, T Stützle Aaai 7, 1152-1157, 2007	387	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	371	2005
Reasoning With Conditional Ceteris Paribus Preference Statements. C Boutilier, RI Brafman, HH Hoos, D Poole UAI 99, 71-80, 1999	362	1999
Solving combinatorial auctions using stochastic local search HH Hoos, C Boutilier Aaai/iaai, 22-29, 2000	345	2000

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