Deep Learning Theory Workshop 2025

Description

The Deep Learning Theory Workshop 2025 is organized by the Deep Learning Theory Team at RIKEN AIP, and aims to foster in-depth discussions and collaborations at the intersection of deep learning practice and theory.

This workshop brings together leading researchers from Japan and around the world, including both academic experts and members of our team, to discuss recent advances, open problems, and emerging trends in the theoretical understanding of deep learning.

While deep learning continues to achieve remarkable success across a wide range of applications, the theoretical foundations behind these breakthroughs are still being actively explored. Questions around generalization, optimization, representation, and robustness remain central to developing a principled understanding of modern deep learning systems.

We invite contributions and participation from researchers in learning theory, machine learning, statistics, information theory, and related fields, with the goal of building bridges between theoretical analysis and practical advances in deep learning.

Schedule

Day 1 (Aug 5)
10:00–10:50 Taiji Suzuki

10:50–11:40 Murat Erdogdu

11:40–13:30 Working Lunch
13:30–14:20 Fenglei Fan

14:20–15:10 Shinho Chewi

15:10–15:40 Coffee break

15:40–16:30 Mahdi Soltanolkotabi

16:30–17:30 Denny Wu

17:30–18:30 Poster session
18:30– Dinner time

Day 2(Aug 6)
10:00–10:50 Atsushi Nitanda

10:50–11:40 Yuan Cao

11:40–13:30 Working Lunch
13:30–14:20 Wei Huang

14:20–15:10 Fanghui Liu

15:10–15:40 Coffee break

15:40–16:30 Matus Telgarsky

16:30–17:20 Takashi Furuya

18:00– Working Dinner

Day 3(Aug 7)
10:00–10:50 Han Bao

10:50–11:40 Sho Sonoda

11:40–11:50 Closing remark