Multiobjective tree-structured Parzen estimator Y Ozaki, Y Tanigaki, S Watanabe, M Nomura, M Onishi Journal of Artificial Intelligence Research 73, 1209-1250, 2022 | 52 | 2022 |
Warm Starting CMA-ES for Hyperparameter Optimization M Nomura, S Watanabe, Y Akimoto, Y Ozaki, M Onishi Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 9188-9196, 2021 | 37 | 2021 |
CMA-ES with margin: Lower-bounding marginal probability for mixed-integer black-box optimization R Hamano, S Saito, M Nomura, S Shirakawa Proceedings of the genetic and evolutionary computation conference, 639-647, 2022 | 24 | 2022 |
Distance-weighted Exponential Natural Evolution Strategy for Implicitly Constrained Black-Box Function Optimization M Nomura, N Sakai, N Fukushima, I Ono 2021 IEEE Congress on Evolutionary Computation (CEC), 1099-1106, 2021 | 9 | 2021 |
Towards Resolving Propensity Contradiction in Offline Recommender Learning Y Saito, M Nomura IJCAI 2022, 2022 | 8 | 2022 |
Efficient hyperparameter optimization under multi-source covariate shift M Nomura, Y Saito Proceedings of the 30th ACM International Conference on Information …, 2021 | 7* | 2021 |
機械学習におけるハイパパラメータ最適化手法: 概要と特徴 尾崎嘉彦, 野村将寛, 大西正輝 電子情報通信学会論文誌 D 103 (9), 615-631, 2020 | 7 | 2020 |
Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes S Takeno, M Nomura, M Karasuyama Proceedings of the International Conference on Machine Learning 202, 33516-33533, 2023 | 5 | 2023 |
Fast moving natural evolution strategy for high-dimensional problems M Nomura, I Ono 2022 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2022 | 4 | 2022 |
Towards a principled learning rate adaptation for natural evolution strategies M Nomura, I Ono International Conference on the Applications of Evolutionary Computation …, 2022 | 4 | 2022 |
Off-policy evaluation of slate bandit policies via optimizing abstraction H Kiyohara, M Nomura, Y Saito arXiv preprint arXiv:2402.02171, 2024 | 3 | 2024 |
cmaes: A Simple yet Practical Python Library for CMA-ES M Nomura, M Shibata arXiv preprint arXiv:2402.01373, 2024 | 3 | 2024 |
CMA-ES with Learning Rate Adaptation: Can CMA-ES with Default Population Size Solve Multimodal and Noisy Problems? M Nomura, Y Akimoto, I Ono Proceedings of the Genetic and Evolutionary Computation Conference, 839–847, 2023 | 3 | 2023 |
Benchmarking CMA-ES with margin on the bbob-mixint testbed R Hamano, S Saito, M Nomura, S Shirakawa Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022 | 3 | 2022 |
Natural evolution strategy for unconstrained and implicitly constrained problems with ridge structure M Nomura, I Ono 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2021 | 3 | 2021 |
Evaluating initialization of nelder-mead method for hyperparameter optimization in deep learning S Takenaga, S Watanabe, M Nomura, Y Ozaki, M Onishi, H Habe 2020 25th International Conference on Pattern Recognition (ICPR), 3372-3379, 2021 | 3 | 2021 |
Best Arm Identification with a Fixed Budget under a Small Gap M Kato, K Ariu, M Imaizumi, M Uehara, M Nomura, C Qin stat 1050, 11, 2022 | 2 | 2022 |
CMA-ES with Learning Rate Adaptation M Nomura, Y Akimoto, I Ono arXiv preprint arXiv:2401.15876, 2024 | 1 | 2024 |
Marginal Probability-Based Integer Handling for CMA-ES Tackling Single-and Multi-Objective Mixed-Integer Black-Box Optimization R Hamano, S Saito, M Nomura, S Shirakawa ACM Transactions on Evolutionary Learning, 2024 | 1 | 2024 |
(1+ 1)-CMA-ES with Margin for Discrete and Mixed-Integer Problems Y Watanabe, K Uchida, R Hamano, S Saito, M Nomura, S Shirakawa Proceedings of the Genetic and Evolutionary Computation Conference, 882–890, 2023 | 1 | 2023 |