This event is part of Theoretical Advances in Reinforcement Learning and Control View Details

Frontiers in Online Reinforcement Learning

David Rubenstein Forum - 1201 E 60th St, Chicago, IL 60637

Description

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This workshop highlights recent advances in online reinforcement learning (RL), with a focus on its connections to emerging technologies like large language models (LLMs). As machine learning systems grow more capable, online RL can further enhance their task specific capabilities.

Participants will explore the evolving RL landscape, discuss its integration with large-scale models, and examine challenges and opportunities at this intersection. Join us to engage with cutting-edge ideas shaping the future of online reinforcement learning.

Organizers

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A Z
Andrea Zanette Carnegie Mellon University
L Y
Lin Yang University of California, Los Angeles (UCLA)

Speakers

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R A
Rishabh Agarwal Periodic Labs
K B
Kianté Brantley Harvard University
B E
Benjamin Eysenbach Princeton University
A K
Aviral Kumar Carnegie Mellon University
A P
Aldo Pacchiano Boston University
A S
Ayush Sekhari Boston University
L S
Laixi Shi Johns Hopkins University
Y S
Yuda Song Carnegie Mellon University
W S
Wen Sun Cornell University
G S
Gokul Swamy Carnegie Mellon University
C S
Csaba Szpezavari Deepmind and University of Alberta
A W
Andrew Wagenmaker University of California, Berkeley
M U
Masatoshi Uehara Evolutionary Scale
Z Y
Zhuoran Yang Yale University
M Y
Ming Yin Georgia Tech
X Z
Xuezhou Zhang Boston University
B Z
Banghua Zhu University of Washington and NVIDIA

Registration

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