Transfer learning, from medical data analysis to reinforcement learning

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• Xin Guo (University of California, Berkeley)
• Thursday 19 March 2026, 14:00-15:00
• Seminar Room 1, Newton Institute.

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SCLW02 - Reinforcement Learning for Science: Discovery and Automation

Transfer learning is a machine learning technique that leverages knowledge acquired in one domain to enhance performance on a related task. This technique has been adopted in financial data and medical data analysis.It plays a central role in the success of large language models (LLMs) such as GPT and BERT .  In this talk, I will discuss how reinforcement learning (RL), and in particular continuous time RL, can benefit from transfer learningprinciples.  

This talk is part of the Isaac Newton Institute Seminar Series series.

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