Holger Hoos

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Thomas StützleF.R.S.-FNRS Research Director, Université Libre de Bruxelles (ULB)Verified email at ulb.ac.be
Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI ChairVerified email at cs.ubc.ca
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
Ronen BrafmanDepartment of Computer Science, Ben-Gurion UniversityVerified email at cs.bgu.ac.il
Marius LindauerLeibniz University Hannover (Germany)Verified email at tnt.uni-hannover.de
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
Alan J. HuProfessor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
Sam BaylessUniversity of British ColumbiaVerified email at cs.ubc.ca
Kevin MurphyResearch Scientist, GoogleVerified email at google.com
Heike TrautmannProfessor of Data Science: Statistics and Optimization, Department of Information SystemsVerified email at wi.uni-muenster.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


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	4257	2000
Sequential model-based optimization for general algorithm configuration F Hutter, HH Hoos, K Leyton-Brown International conference on learning and intelligent optimization, 507-523, 2011	2395	2011
Stochastic local search: Foundations and applications HH Hoos, T Stützle Elsevier, 2004	2236	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	1529	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	1369	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	1182	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	1105	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	988	2008
A survey on semi-supervised learning JE Van Engelen, HH Hoos Machine Learning 109 (2), 373-440, 2020	810	2020
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	666	2017
Critical assessment of automated flow cytometry data analysis techniques N Aghaeepour, G Finak, H Hoos, TR Mosmann, R Brinkman, R Gottardo, ... Nature methods 10 (3), 228-238, 2013	588	2013
Improvements on the Ant-System: Introducing the MAX-MIN Ant System T Stützle, H Hoos Artificial neural nets and genetic algorithms, 245-249, 1998	488	1998
Algorithm runtime prediction: Methods & evaluation F Hutter, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 206, 79-111, 2014	469	2014
SATLIB: An online resource for research on SAT HH Hoos, T Stützle Sat 2000, 283-292, 2000	437	2000
Automatic algorithm configuration based on local search F Hutter, HH Hoos, T Stützle Aaai 7, 1152-1157, 2007	374	2007
An ant colony optimisation algorithm for the 2D and 3D hydrophobic polar protein folding problem A Shmygelska, HH Hoos BMC bioinformatics 6 (1), 1-22, 2005	364	2005
An efficient approach for assessing hyperparameter importance F Hutter, H Hoos, K Leyton-Brown	359	2014
Reasoning With Conditional Ceteris Paribus Preference Statements. C Boutilier, RI Brafman, HH Hoos, D Poole UAI 99, 71-80, 1999	357	1999
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	345	2013
Solving combinatorial auctions using stochastic local search HH Hoos, C Boutilier Aaai/iaai, 22-29, 2000	339	2000

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