| 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 | 451 | 2019 |
| Multi-information source optimization M Poloczek, J Wang, P Frazier Advances in neural information processing systems 30, 2017 | 269 | 2017 |
| Bayesian optimization with gradients J Wu, M Poloczek, AG Wilson, PI Frazier Proceedings of the 31st International Conference on Neural Information …, 2017 | 262 | 2017 |
| Bayesian optimization of combinatorial structures R Baptista, M Poloczek Proceedings of the 35th International Conference on Machine Learning 80, 462 …, 2018 | 153 | 2018 |
| A framework for Bayesian optimization in embedded subspaces A Nayebi, A Munteanu, M Poloczek International Conference on Machine Learning, 4752-4761, 2019 | 142 | 2019 |
| Scalable constrained Bayesian optimization D Eriksson, M Poloczek International Conference on Artificial Intelligence and Statistics, 730-738, 2021 | 109 | 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 | 103 | 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 | 75 | 2018 |
| Warm starting Bayesian optimization M Poloczek, J Wang, PI Frazier 2016 Winter simulation conference (WSC), 770-781, 2016 | 64 | 2016 |
| 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 |
| 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 | 40 | 2017 |
| Cost-effective materials discovery: Bayesian optimization across multiple information sources HC Herbol, M Poloczek, P Clancy Materials Horizons 7 (8), 2113-2123, 2020 | 35 | 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 | 31 | 2021 |
| Bounds on greedy algorithms for MAX SAT M Poloczek European Symposium on Algorithms, 37-48, 2011 | 27 | 2011 |
| Contagious sets in dense graphs D Freund, M Poloczek, D Reichman European Journal of Combinatorics 68, 66-78, 2018 | 24 | 2018 |
| Bayesian optimization allowing for common random numbers MAL Pearce, M Poloczek, J Branke Operations Research 70 (6), 3457-3472, 2022 | 21* | 2022 |
| 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 |
| 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 | 20 | 2019 |
| 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 | 19 | 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 | 19 | 2019 |
Peter I FrazierAssociate Professor of Operations Research and Information Engineering, Cornell University在 cornell.edu 的电子邮件经过验证
