[ISPI2024 closed on a high note. Thank you for your participation!] DAIKIN International Symposium on Physics of Intelligence-- Statistical Mechanics and Machine Learning: A Powerful Combination for Data Analysis --

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

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