Submission: https://forms.gle/MJuSJHJpuJ3mFevf6
Workshop Theme: "Deep Reinforcement Learning: Bridging Theory and Practice" https://isaim-deeprl.github.io/2024/
Dates & Venue: January 8, 9, 2024, collocated with the International Symposium on Artificial Intelligence and Mathematics (ISAIM), Fort Lauderdale, FL.
Overview:
Deep Reinforcement Learning (DRL) stands at the forefront of AI research, shaping the future of diverse fields from robotics to finance. However, the journey from theoretical foundations to practical applications in DRL is laden with challenges. Our workshop, a special session of ISAIM 2024, aims to address these challenges by fostering a deeper understanding and appreciation of the latest advancements in DRL. We will discuss a variety of talks (including but not limited to) sample efficiency, exploration vs. exploitation, transfer learning, stability and convergence, and real-world application barriers.
Invited Speakers:
Benjamin Eysenbach (Princeton)
Aviral Kumar (CMU / Google)
Pulkit Agrawal (MIT)
Chi Jin (Princeton)
Sanjiban Choudhury (Cornell)
Wen Sun (Cornell)
Kaiqing Zhang (UMD)
Max Simchowitz (MIT)
Animesh Garg (Georgia Tech)
Zhuoran Yang (Yale)
Objective:
Our goal is to illuminate the connection between the theoretical and practical aspects of DRL, addressing inherent challenges in the field. Participants will gain comprehensive knowledge, backed by expert-led discussions, talks and lively interaction.
Target Audience:
This workshop is ideal for researchers, AI practitioners, graduate students, and industry professionals keen on exploring the forefront of Deep Reinforcement Learning.
Call for Posters:
We invite submissions for poster presentations that align with the theme of the workshop. This is an excellent opportunity to showcase your research, share novel ideas, and interact with experts in the field. There will be a lot of engaging discussion and all relevant work is welcome!
Submission Guidelines:
Poster topics should be relevant to DRL and its challenges. But this is defined very broadly, please submit if you think at all relevant!
Abstracts should be concise, clearly outlining objectives, methodology, and findings.
Include author(s) name, affiliation, and contact information.
Flexible on format, 4+ page papers accepted!
Submission Deadline: Jan 5, 2024
Contact Information: zhaoranwang@gmail.com or abhgupta@cs.washington.edu
Join us in exploring the intricate world of DRL and contribute to bridging the gap between theory and practice. We look forward to your insightful contributions and lively discussions!
Organizers: Abhishek Gupta (UW), Zhaoran Wang (Northwestern), Aldo Pacchiano (Boston University / Broad Institute), Claudio Gentile (Google)
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