Ep. 3: Sam Hopkins

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Probably Approximately Correct Learners

Chara Podimata

3 episodes

3 days ago

Welcome to Probably Approximately Correct Learners, a podcast from the Learning Theory Alliance team. In this podcast, we will dive deep into the minds of leading researchers in Machine Learning! Join us for engaging interviews that explore a diverse range of topics—from groundbreaking research findings to the experiences and insights that shape life beyond academia. Whether you're a seasoned expert or just starting your journey in the field, this podcast is your gateway to understanding the evolving landscape of Machine Learning. Tune in and broaden your perspective with each episode!

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Ep. 3: Sam Hopkins

Probably Approximately Correct Learners

1 hour 1 minute 29 seconds

1 month ago

Ep. 3: Sam Hopkins

Welcome to Probably Approximately Correct Learners Episode 3! In this episode, Chara chats with Professor Sam Hopkins.

Sam is a theoretical computer scientist and Assistant Professor at MIT, in the Theory of Computing group in the Department of Electrical Engineering and Computer Science, where he holds the Jamieson Career Development Chair. His interests include algorithms, theory of machine learning, semidefinite programming, sum of squares method, and bicycles.

Before MIT, he was a Miller fellow in the theory of computing group at UC Berkeley, hosted by Prasad Raghavendra and Luca Trevisan. Before that, he got his PhD at Cornell, advised by David Steurer.