Uploaded April 2024 | Updated September 2026, 2 weeks ago
2024年3月3日、サントリーホールディングスの新浪剛史社長が代表幹事を務める経済同友会と沖縄経済同友会のメンバー37人がOISTを訪れ、イベントを開催しました。
イベントは、新浪社長とカリン・マルキデスOIST学長の挨拶で始まりました。また、OISTの河野恵子准教授と根本香絵教授によるプレゼンテーション、質疑応答、パネルディスカッションが行われました。
パネルディスカッションでは、南部智一 経済同友会 先端科学技術戦略検討委員会 委員長(住友商事 顧問)がモデレーターを務め、本永浩之 沖縄経済同友会 代表幹事(沖縄電力株式会社 代表取締役社長)、ギル・グラノットマイヤー OIST首席副学長(技術開発イノベーション担当)、間下直晃 経済同友会 副代表幹事(ブイキューブ 代表取締役会長 グループCEO )がパネリストを務めました。
2024年3月3日、サントリーホールディングスの新浪剛史社長が代表幹事を務める経済同友会と沖縄経済同友会のメンバー37人がOISTを訪れ、イベントを開催しました。
イベントは、新浪社長とカリン・マルキデスOIST学長の挨拶で始まりました。また、OISTの河野恵子准教授と根本香絵教授によるプレゼンテーション、質疑応答、パネルディスカッションが行われました。
パネルディスカッションでは、南部智一 経済同友会 先端科学技術戦略検討委員会 委員長(住友商事 顧問)がモデレーターを務め、本永浩之 沖縄経済同友会 代表幹事(沖縄電力株式会社 代表取締役社長)、ギル・グラノットマイヤー OIST首席副学長(技術開発イノベーション担当)、間下直晃 経済同友会 副代表幹事(ブイキューブ 代表取締役会長 グループCEO )がパネリストを務めました。




![Florian Yger: A Geometric Adventure in Machine Learning (TSVP Talk at OIST)
[Title]
Florian Yger - A Geometric Adventure in Machine Learning: Learning with Invariances, Structures, and Prior Knowledge (TSVP Talk at OIST)
[Description]
Florian Yger is visiting OIST from 2024-05-20 until 2024-08-15 through the Theoretical Sciences Visiting Program (TSVP). Find out more about the TSVP on the program website:
https://www.oist.jp/visiting-program.
Abstract: In this presentation, we embark on a journey through the landscapes of machine learning, focusing on the role of representation learning. Traditional approaches often restrict themselves to Euclidean spaces, yet many real-world data, such as graphs and covariances, defy this simplistic framework. We explore how embracing non-Euclidean geometries—specifically curved spaces like Riemannian manifolds—unlocks new possibilities in understanding and predicting structured data. This framework allows for the incorporation of prior knowledge such as constraints and invariances into machine learning algorithms.
Central to our exploration is the Fréchet averaging problem, a fundamental tool that generalizes the well-know average to metric spaces. From this cornerstone, we derive many extensions ranging from graph averaging to dimensionality reduction on Riemannian manifolds. We illustrate their practical implications through numerical experiments on biomedical data.
Motivated by challenging applications, this presentation not only highlights the limitations of Euclidean-centric approaches but also underscores the potential of geometry-aware representation learning. Join us as we navigate this geometric adventure into the curved realm of geometry-aware representation learning.
Profile: Florian Yger is an associate professor at Université Paris-Dauphine since 2015, teaching Data Analysis and Machine Learning in the department MIDO. Within the LAMSADE, he is part of the team MILES which focuses on trustworthy Machine Learning and Explainable AI. From 2014 to 2015, he was a JSPS postdoctoral fellow in the laboratory of Prof. Sugiyama at Tokyo University. He received his PhD in Computer science from LITIS, Université de Rouen under the supervision of Alain Rakotomamonjy in 2013. He contributes to the problem of representation learning with a particular interest in the representation of structured data (graphs, covariance matrices,…) and the development of learning algorithm for non-Euclidean spaces. This work has many applications ranging from signal processing (EEG signals and Brain Computer Interface) and to image processing (Paintings for art style recognition). More recently, within MILES teams, he addresses the questions of trust, explainability and interpretability in machine learning models with a focus counterfactual reasoning on data. He recently started studying the interplay between computational social choice and machine learning in the context of voter’s opinion aggregation. He is a visiting researcher at RIKEN AIP, Japan since 2017, is a member of the Prairie (PaRis Artificial Intelligence Research InstitutE) where he holds a junior chair, and an Affiliate of the Theoretical Sciences Visiting Program (TSVP) at OIST.
#OIST #OIST_TSVP #MachineLearning #Geometry #Manifolds #Theoretical #Science #VisitingProgram #Okinawa #TSVP Florian Yger: A Geometric Adventure in Machine Learning (TSVP Talk at OIST)](https://i.ytimg.com/vi/KlU1mS1xr3I/mqdefault.jpg)





