| Presentation | 2019-06-17 A Comparison of Surrogate Models in Bayesian Optimization Sho Shimoyama, Masahiro Nomura, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Bayesian optimization can efficiently select the next search point by using a surrogate model that estimates an objective function from past data, so it is used in various fields including hyperparameter optimization of machine learning algorithms. Although Gaussian process and random forest are the representative surrogate models in Bayesian optimization, effects of properties of these surrogate models on the performance are not sufficiently discussed. In this study, we examine the effects of properties of these surrogate models on the performance by experiments on benchmark functions with different noise levels, number of dimensions and characteristics. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Bayesian optimization / Gaussian process / random forest / expected improvement |
| Paper # | IBISML2019-7 |
| Date of Issue | 2019-06-10 (IBISML) |
| Conference Information | |
| Committee | NC / IBISML / IPSJ-MPS / IPSJ-BIO |
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| Conference Date | 2019/6/17(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okinawa Institute of Science and Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Neurocomputing, Machine Learning Approach to Biodata Mining, and General |
| Chair | Hayaru Shouno(UEC) / Hisashi Kashima(Kyoto Univ.) / Masakazu Sekijima(Tokyo Tech) / Hiroyuki Kurata(Kyutech) |
| Vice Chair | Kazuyuki Samejima(Tamagawa Univ) / Masashi Sugiyama(Univ. of Tokyo) / Koji Tsuda(Univ. of Tokyo) |
| Secretary | Kazuyuki Samejima(NAIST) / Masashi Sugiyama(NTT) / Koji Tsuda(Nagoya Inst. of Tech.) / (AIST) / (Nagoya Univ.) |
| Assistant | Takashi Shinozaki(NICT) / Ken Takiyama(TUAT) / Tomoharu Iwata(NTT) / Shigeyuki Oba(Kyoto Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Neurocomputing / Technical Committee on Infomation-Based Induction Sciences and Machine Learning / IPSJ Special Interest Group on Mathematical Modeling and Problem Solving / IPSJ Special Interest Group on Bioinformatics and Genomics |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Comparison of Surrogate Models in Bayesian Optimization |
| Sub Title (in English) | |
| Keyword(1) | Bayesian optimization |
| Keyword(2) | Gaussian process |
| Keyword(3) | random forest |
| Keyword(4) | expected improvement |
| 1st Author's Name | Sho Shimoyama |
| 1st Author's Affiliation | Meiji University(Meiji Univ.) |
| 2nd Author's Name | Masahiro Nomura |
| 2nd Author's Affiliation | CyberAgent, Inc.(CA) |
| Date | 2019-06-17 |
| Paper # | IBISML2019-7 |
| Volume (vol) | vol.119 |
| Number (no) | IBISML-89 |
| Page | pp.pp.43-50(IBISML), |
| #Pages | 8 |
| Date of Issue | 2019-06-10 (IBISML) |