Machine Learning Theory with Leslie Valiant

What would a "theory" of machine learning tell us? In this episode Tom meets with the person who invented what is now the widely accepted definition of supervised machine learning: Turing Award recipient and Harvard Professor Leslie Valiant.

Leslie tells us how he got interested in the problem, his contribution, the evolution of machine learning theory over the decades, and his advice to new researchers.

Creators and Guests

Host

Tom Mitchell

Tom Mitchell is the University Founders Professor at Carnegie Mellon University, a Digital Fellow at the Stanford Digital Economy Lab, and the author of Machine Learning, a foundational textbook on the subject.

LV

Guest

Leslie Valiant

T. Jefferson Coolidge Professor of Computer Science and Applied Mathematics, Harvard University

Producer

Matty Smith

Writer/director/editor from Los Angeles, with experience writing and directing scripted television and national commercials. Mixed media producer with hands-on experience in all areas of production.

What is Machine Learning: How Did We Get Here??

Tom Mitchell literally wrote the book on machine learning. In this series of candid conversations with his fellow pioneers, Tom traces the history of the field through the people who built it. Behind the tech are stories of passion, curiosity, and humanity.

Tom Mitchell is the University Founders Professor at Carnegie Mellon University, a Digital Fellow at the Stanford Digital Economy Lab, and the author of Machine Learning, a foundational textbook on the subject. This podcast is produced by the Stanford Digital Economy Lab.