Events Calendar

CS Colloquium: Chris J. C. Burges (Microsoft Research )

Speaker: Chris J. C. Burges , Microsoft Research

Talk Title: From Machine Learning to Machine Comprehension? Plus, two challenge datasets, and a family relations model.

Series: CS Colloquium

Abstract: Will current Machine Learning approaches be sufficient to solve the problem of the machine comprehension of text? First I will explain why, despite its recent successes in attacking several basic problems in AI, I think that the answer is "probably not". Then I will describe two datasets that we recently created to spur research on this problem. Finally I will describe recent work on modeling relations between relations, as instantiated by a model of human family relations.

Biography: After a checkered past involving first theoretical physics and then systems engineering at Bell Labs, Chris Burges saw a cool demo of a neural network reading handwritten digits: this triggered his long descent into machine learning. He has worked on handwriting and machine print recognition (he worked on a system now used to read millions of checks daily, and on Zip code and handwritten address recognition for the USPS), support vector machines, audio fingerprinting (his work is currently used in XBox and Windows Media Player to identify music), speaker verification, and information retrieval. His ranking algorithm is currently used by Bing for web search. Chris manages the Machine Learning and Intelligence group at Microsoft Research. He was program co-chair of Neural Information Processing Systems 2012 and general co-chair of NIPS 2013. His main current research interest is on modeling meaning in language.

Host: Fei Sha

Location: Henry Salvatori Computer Science Center (SAL) - 101

Audiences: Everyone Is Invited

Contact: Assistant to CS chair