Probability and Prejudice: Bridging the Gap Between Machine Learning and Programming Languages

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• Neil Toronto, University of Maryland
• Friday 17 April 2015, 10:00-11:00
• SS03.

If you have a question about this talk, please contact Raphael Proust.

Probabilistic programming languages are often thought of as a point of intersection between machine learning and programming languages. While this is true in some respects, they mostly occupy a gap between the two research areas. Technically, correctly running all probabilistic programs requires different algorithms, formalisms and theory than are commonly used in either area. Culturally, the gap is perhaps wider: each area has its own vocabulary, ideals, standards of rigor, and motivations, which are often at odds.

In this talk, I’ll describe how I crossed the gap from machine learning to programming languages, and how I’m building a bridge back to the other side.

This talk is part of the Computer Laboratory Programming Research Group Seminar series.

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• All Talks (aka the CURE list)
• Cambridge talks
• Computer Laboratory Programming Research Group Seminar
• Department of Computer Science and Technology talks and seminars
• Interested Talks
• SS03
• School of Technology
• Trust & Technology Initiative - interesting events
• bld31

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