Matthias Poloczek

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Peter I FrazierAssociate Professor of Operations Research and Information Engineering, Cornell UniversityVerified email at cornell.edu
Michael PearceSenior Researcher, BelfastVerified email at warwick.ac.uk
David ErikssonResearch Scientist Manager at MetaVerified email at fb.com
Jacob GardnerUniversity of PennsylvaniaVerified email at seas.upenn.edu
Jialei WangCornell UniversityVerified email at cornell.edu
Henry HerbolUniversal Display CorporationVerified email at cornell.edu
David P. WilliamsonProfessor of Operations Research, Cornell UniversityVerified email at cornell.edu
Juergen BrankeProfessor of Operational Research and Systems, Warwick Business SchoolVerified email at wbs.ac.uk
Andrew Gordon WilsonNew York UniversityVerified email at cims.nyu.edu
Jian WuCornell UniversityVerified email at cornell.edu
Anke van ZuylenCornell UniversityVerified email at cornell.edu
Alexander MunteanuTU Dortmund UniversityVerified email at tu-dortmund.de
Amin Nayebi NodoushanSystems and Industrial Engineering, University of ArizonaVerified email at email.arizona.edu
Ricardo BaptistaCalifornia Institute of TechnologyVerified email at caltech.edu
Luigi NardiAssociate Professor in Machine Learning at Lund UniversityVerified email at cs.lth.se
Leonard PapenmeierLund UniversityVerified email at cs.lth.se
Karen WillcoxOden Institute for Computational Engineering and Sciences, UT AustinVerified email at oden.utexas.edu
Rémi LamDeepMindVerified email at deepmind.com
Mario SzegedyProfessor of Computer Science, Rutgers UniversityVerified email at cs.rutgers.edu
Shane HendersonProfessor of Operations Research and Information Engineering, Cornell UniversityVerified email at cornell.edu

Matthias Poloczek

Principal Scientist at Amazon

Verified email at cornell.edu

Machine Learning Bayesian Optimization AutoML Bandits


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Scalable global optimization via local bayesian optimization D Eriksson, M Pearce, JR Gardner, R Turner, M Poloczek Advances in Neural Information Processing Systems (NeurIPS), 2019	539	2019
Bayesian optimization with gradients J Wu, M Poloczek, AG Wilson, PI Frazier Proceedings of the 31st International Conference on Neural Information …, 2017	284	2017
Multi-information source optimization M Poloczek, J Wang, P Frazier Advances in neural information processing systems 30, 2017	280	2017
A framework for Bayesian optimization in embedded subspaces A Nayebi, A Munteanu, M Poloczek International Conference on Machine Learning, 4752-4761, 2019	164	2019
Bayesian optimization of combinatorial structures R Baptista, M Poloczek Proceedings of the 35th International Conference on Machine Learning 80, 462 …, 2018	159	2018
Scalable constrained Bayesian optimization D Eriksson, M Poloczek International Conference on Artificial Intelligence and Statistics, 730-738, 2021	125	2021
Efficient search of compositional space for hybrid organic–inorganic perovskites via Bayesian optimization HC Herbol, W Hu, P Frazier, P Clancy, M Poloczek npj Computational Materials 4 (1), 51, 2018	109	2018
Advances in Bayesian optimization with applications in aerospace engineering R Lam, M Poloczek, P Frazier, KE Willcox 2018 AIAA Non-Deterministic Approaches Conference, 1656, 2018	83	2018
Warm starting Bayesian optimization M Poloczek, J Wang, PI Frazier 2016 Winter simulation conference (WSC), 770-781, 2016	71	2016
Greedy algorithms for the maximum satisfiability problem: Simple algorithms and inapproximability bounds M Poloczek, G Schnitger, DP Williamson, A Van Zuylen SIAM Journal on Computing 46 (3), 1029-1061, 2017	42	2017
Randomized greedy algorithms for the maximum matching problem with new analysis M Poloczek, M Szegedy 2012 IEEE 53rd Annual Symposium on Foundations of Computer Science, 708-717, 2012	42	2012
Cost-effective materials discovery: Bayesian optimization across multiple information sources HC Herbol, M Poloczek, P Clancy Materials Horizons 7 (8), 2113-2123, 2020	39	2020
Tuning materials-binding peptide sequences toward gold-and silver-binding selectivity with bayesian optimization ZE Hughes, MA Nguyen, J Wang, Y Liu, MT Swihart, M Poloczek, ... ACS nano 15 (11), 18260-18269, 2021	36	2021
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces L Papenmeier, L Nardi, M Poloczek Advances in Neural Information Processing Systems 35, NeurIPS 2022, 2022	31	2022
Bounds on greedy algorithms for MAX SAT M Poloczek European Symposium on Algorithms, 37-48, 2011	28	2011
Contagious sets in dense graphs D Freund, M Poloczek, D Reichman European Journal of Combinatorics 68, 66-78, 2018	26	2018
Bayesian optimization allowing for common random numbers MAL Pearce, M Poloczek, J Branke Operations Research 70 (6), 3457-3472, 2022	22*	2022
Bypassing solid-state intermediates by solvent engineering the crystallization pathway in hybrid organic–inorganic perovskites AG Ortoll-Bloch, HC Herbol, BA Sorenson, M Poloczek, LA Estroff, ... Crystal Growth & Design 20 (2), 1162-1171, 2019	21	2019
Fast reconfigurable antenna state selection with hierarchical thompson sampling T Zhao, M Li, M Poloczek ICC 2019-2019 IEEE International Conference on Communications (ICC), 1-6, 2019	21	2019
Randomized variants of Johnson's algorithm for MAX SAT M Poloczek, G Schnitger Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete …, 2011	21	2011

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