Events Calendar

AAAI@USC Presents: Machine Learning@Google Tech Talk

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Title: From Text to Concepts at Google

Abstract: This talk will describe Rephil, a system used widely within Google to identify the concepts or topics that underlie a given piece of text. Rephil determines, for example, that "apple pie" relates to some of the same concepts as "chocolate cake", but has little in common with "apple ipod". The concepts used by Rephil are not pre-specified; instead, they are derived by an unsupervised learning algorithm running on massive amounts of text. The result of this learning process is a Rephil model -- a giant Bayesian network with concepts as nodes. I will discuss the structure of Rephil models, the distributed machine learning algorithm that we use to build these models from terabytes of data, and the Bayesian network inference algorithm that we use to identify concepts in new texts under tight time constraints. I will also discuss how Rephil relates to ongoing academic research on probabilistic topic models.

Bio: Brian Milch is a software engineer at Google's Los Angeles office. He first joined Google in 2000, after completing a B.S. in Symbolic Systems at Stanford University. A year later, he entered the Computer Science Ph.D. program at U.C. Berkeley. He received his doctorate in 2006, with a thesis focused on the integration of probabilistic and logical approaches to artificial intelligence. He then spent two years as a post-doctoral researcher at MIT before returning to Google in 2008. He has contributed to Google production systems for spelling correction, transliteration, and semantic modeling of text.

After the talk, Brian will also be happy to answer questions about both the technical material and what it's like to work on machine learning at Google.

---Free Pizzas and Google swags will be provided---

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Location: Mark Taper Hall Of Humanities (THH) - 101

Audiences: Everyone Is Invited

Contact: Giovanni Sutanto