Holger Hoos

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Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI ChairVerified email at cs.ubc.ca
Frank HutterELLIS Institute Tübingen & Professor, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Thomas StützleF.R.S.-FNRS Research Director, Université Libre de Bruxelles (ULB)Verified email at ulb.ac.be
Lin XuNETINT, University of British ColumbiaVerified email at cs.ubc.ca
Anne CondonProfessor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
Craig BoutilierPrincipal Scientist, GoogleVerified email at google.com
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Dave A. D. TompkinsLecturer, Computer Science, University of WaterlooVerified email at uwaterloo.ca
Marius LindauerLeibniz University Hannover (Germany), Institute of Artificial Intelligence LUH|AI, L3S ResearchVerified email at ai.uni-hannover.de
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
Nima AghaeepourStanford UniversityVerified email at stanford.edu
Ryan BrinkmanBritish Columbia Cancer AgencyVerified email at bccrc.ca
David PooleProfessor of Computer Science, University of British ColumbiaVerified email at cs.ubc.ca
Torsten SchaubUniversity of PotsdamVerified email at cs.uni-potsdam.de
Jesper van EngelenAutonomous Vehicles at NVIDIA, previously Leiden University and ETH ZürichVerified email at liacs.nl
Jan N. van RijnLeiden UniversityVerified email at liacs.leidenuniv.nl
Heike TrautmannProfessor of Machine Learning and Optimisation, Paderborn University, GermanyVerified email at uni-paderborn.de
Carmel DomshlakProfessor, TechnionVerified email at ie.technion.ac.il
Sam BaylessUniversity of British Columbia, Amazon Web ServicesVerified 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	4566	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	3430	2011
A survey on semi-supervised learning JE Van Engelen, HH Hoos Machine learning 109 (2), 373-440, 2020	2866	2020
Stochastic local search HH Hoos, T Stϋtzle Handbook of Approximation Algorithms and Metaheuristics, 297-307, 2018	2528	2018
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	2152	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	1478	1997
ParamILS: an automatic algorithm configuration framework F Hutter, HH Hoos, K Leyton-Brown, T Stützle Journal of artificial intelligence research 36, 267-306, 2009	1309	2009
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	1272	2004
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	1192	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	1007	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	689	2013
An efficient approach for assessing hyperparameter importance F Hutter, H Hoos, K Leyton-Brown	659	2014
Algorithm runtime prediction: Methods & evaluation F Hutter, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 206, 79-111, 2014	598	2014
SATLIB: An online resource for research on SAT HH Hoos, T Stützle Sat 2000, 283-292, 2000	518	2000
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	510	1998
Automated algorithm selection: Survey and perspectives P Kerschke, HH Hoos, F Neumann, H Trautmann Evolutionary computation 27 (1), 3-45, 2019	509	2019
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), 1-5, 2013	477	2013
Automatic algorithm configuration based on local search F Hutter, HH Hoos, T Stützle Aaai 7, 1152-1157, 2007	416	2007
A research agenda for hybrid intelligence: augmenting human intellect with collaborative, adaptive, responsible, and explainable artificial intelligence Z Akata, D Balliet, M De Rijke, F Dignum, V Dignum, G Eiben, A Fokkens, ... Computer 53 (8), 18-28, 2020	412	2020
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	385	2005

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