Programming with Probabilistic Graphical Models
Recorded 15 December 2014 in Lausanne, Vaud, Switzerland
Event: IC Colloquia - EPFL IC School Colloquia
The increased availability of massive codebases (“Big Code”) creates an exciting opportunity for new kinds of programming tools based on probabilistic models. Enabled by these models, tomorrow’s tools will provide probabilistically likely solutions to programming tasks that are difficult or impossible to solve with traditional techniques.
In this talk, I will present a new approach for building such tools based on structured prediction with graphical models, and in particular, conditional random fields. These are powerful machine learning techniques popular in computer vision -- by connecting these techniques to programs, our work enables new applications not previously possible.
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