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117 - Provably efficient reinforcement learning with Dr. Akshay Krishnamurthy

117 - Provably efficient reinforcement learning with Dr. Akshay Krishnamurthy

Dr. Akshay Krishnamurthy is a leading reinforcement learning researcher based at MSR's New York City lab. In this episode, he sheds light on his work around feedback-driven data collection and developing provably efficient reinforcement learning algorithms. The ultimate aim of his research is to make RL more practical and applicable in the real world and not just confined to labs.

While MSR's New York City lab is known for its cutting-edge RL research, Dr. Krishnamurthy is focused on bridging the gap between theory and practice. His work has huge implications for the future of RL and its practical applications in various domains.

Tune in to this episode to learn about the challenges in RL and how Dr. Krishnamurthy is addressing them to create a lasting impact on the field.

Link to listen: https://open.spotify.com/episode/4SDwZfQN9FxnuVheiMM52b

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Microsoft Research Podcast

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