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

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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 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 Microsoft Research Cambridge, public talks series.

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Faculty of Education, 184 Hills Road, Cambridge, CB2 8PQ, RoomGS1 Computer Laboratory, Room SN08 Craik Marshall Seminar Room

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