Yoshihiko Ozaki, Yuki Tanigaki, Shuhei Watanabe, and Masaki Onishi
Multiobjective Tree-structured Parzen Estimator for Computationally Expensive Optimization Problems
The Genetic and Evolutionary Computation Conference (GECCO) 2020
Yuki Tanigaki, Yoshihiko Ozaki, Shusuke Shigenaka and Masaki Onishi
Evolutionary Multiobjective Optimization for Pedestrian Route Guidance with Multiple Scenarios
IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE (WCCI) 2020
Masahiro Nomura, Shuhei Watanabe, Yoshihiko Ozaki, Masaki Onishi
Warm Starting Method for CMA-ES
Workshop on Meta-Learning (MetaLearn 2019) @NeurIPS 2019
Shuhei Watanabe, Yoshihiko Ozaki, Yoshiaki Bando and Masaki Onishi
Speeding up of the Nelder-Mead Method by Data-driven Speculative Execution
The 5th Asian Conference on Pattern Recognition (ACPR 2019), Nov 2019
Yoshihiko Ozaki and Masaki Onishi - AI Research Center, AIST & GREE, INC
Practical Deep Neural Network Performance Prediction for Hyperparameter Optimization
The Third International Workshop on Automation in Machine Learning (KDD AutoML 2019 Workshop), Aug 2019.
Rex Hsieh(Kanagawa Institute of Technology), Hisashi Sato(Kanagawa Institute of Technology), Akihiko Shirai(GREE VR Studio Lab, GREE, Inc.)
Evaluation of Avatar and Voice Transform in Programming E-Learning Lectures
the 19th ACM International Conference on Intelligent Virtual Agents, Jul 2019.
Yoshihiko Ozaki(AI Research Center, AIST & GREE, Inc.), Shuhei Watanabe(AI Research Center, AIST & The University of Tokyo), Masaki Onishi(AI Research Center, AIST)
Accelerating the Nelder–Mead Method with Predictive Parallel Evaluation
6th ICML Workshop on Automated Machine Learning, Jun 2019.
Shusuke Shigenaka(AI Research Center, AIST), Shunki Takami( University of Tsukuba), Yoshihiko Ozaki(AI Research Center, AIST & GREE, Inc.), Masaki Onishi(AI Research Center, AIST), Tomohisa Yamashita(Hokkaido University), and Itsuki Noda(AI Research Center, AIST)
Evaluation of Optimization for Pedestrian Route Guidance in Real-world Crowded Scene
International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp.2192-2194, May 2019.
渡邊 修平(産業技術総合研究所人工知能研究センター／東京大学工学部システム創成学科 ), 尾崎 嘉彦(産業技術総合研究所人工知能研究センター／グリー株式会社), 大西 正輝(産業技術総合研究所人工知能研究センター)
Nelder-Mead法の並列化による識別器のハイパパラメータチューニングの高速化
研究報告コンピュータビジョンとイメージメディア（CVIM）, Jan 2019.