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
Public events of RIKEN Center for Advanced Intelligence Project (AIP)
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