ISPI2024: Nov. 6-8, 2024 @Koshiba Hall, The University of Tokyo
【Access】
Koshiba Hall (No. 100 in Hongo Campus Map)
Access Map to Hongo Campus
【Objective】
The goal of machine learning is to extract underlying regularities from training data. The objective is no different from that of statistics, which has been developed for 200 years since Laplace. However, in machine learning, the probabilistic models used to extract regularities are nonlinear and have much higher degrees of freedom than previous statistical models. This leads to new challenges, such as the difficulty of computation and the difficulty of performance evaluation in the data analysis. On the other hand, statistical mechanics has greatly developed techniques for dealing with large-degree-of-freedom nonlinear statistical models through the study of gases and magnetic materials. This suggests that statistical mechanics may be useful for solving the new challenges posed by the birth of machine learning. This symposium aims to bring together researchers in data analysis, machine learning, and statistical mechanics to exchange their expertise.
【Program】 Abstract Book
【Speakers】
*plenary talk
※In alphabetical order
| SueYeon Chung | New York University | USA |
| Alexander Hoffmann | University of California, Los Angeles | USA |
| Sosuke Ito | The University of Tokyo | JPN |
| Shinpei Kawaoka | Tohoku University/Kyoto University | JPN |
| Takeshi Kawasaki | Nagoya University | JPN |
| Nobuyasu Koga | Osaka University | JPN |
| Jian Ma | Carnegie Mellon University | USA |
| Hiroshi Makino | Keio University | JPN |
| Marc Mézard * | Università Bocconi | ITA |
| Daiki Nishiguchi | Institute of Science Tokyo | JPN |
| Mor Nitzan | Hebrew University of Jerusalem | ISR |
| Mariko Okada | Imperial College London & Osaka University | JPN |
| Cengiz Pehlevan | Harvard University | USA |
| Gautam Reddy | Princeton University | USA |
| Sunghan Ro | Harvard University | USA |
| Yasushi Sako | RIKEN | JPN |
| Antonio Sclocchi | École polytechnique fédérale de Lausanne | CHE |
| Dominic Skinner | The Flatiron Institute | USA |
| Kaoru Sugimura | The University of Tokyo | JPN |
| Shinsuke Uda | Yamaguchi University | JPN |
| Vincenzo Vitelli | University of Chicago | USA |
| Lei Wang | Chinese Academy of Sciences | CHN |
| Sho Yaida | Meta | USA |
| Hajime Yoshino | Osaka University | JPN |
| Francesco Zamponi | Sapienza University | ITA |
[Poster Session]
Poster session will be held at “Foyer”, the space in front of
the entrance of Koshiba Hall.
The poster size is “A0” format, i.e., 118.9 cm x 84.1 cm.
*List of posters
For detailed information including abstracts, please click HERE for PDF File.
【ISPI2024 Organizing Committee】
Yoshiyuki Kabashima
Kazumasa A. Takeuchi
Kyogo Kawaguchi
【Sponsors】
DAIKIN INDUSTRIES, LTD.
Institute for Physics of Intelligence, The University of Tokyo
JST JPMJCR1912 “Deciphering intracellular phenomena through information flow”
【Contact】
ispi2024[at]ipi-ut.org