Journée Mathematical Foundations of Learning Theory
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|Theory and Algorithms for Large Scaling Ranking Problems|
Tong Zhang (Yahoo Inc.)
2 juin 2006
I will discuss machine learning problems encountered in web search and advertising, and then focus on ranking. In the web search setting, I will talk about training relevance models based on DCG (discounted cumulated gain) optimization. Under this metric, the system output quality is naturally determined by the performance near the top of its rank-list. I will mainly focus on various theoretical issues in this learning problem.
As a related practical illustration, I will talk about optimizing the ranking function of a statistical machine translation system according to the BLEU metric (standard measure of translation quality). Our approach treats machine translation as a black-box, and can optimize millions of system parameters automatically. This has never been attempted before. I will present our method and some results.
(Joint work with David Cossock, Yahoo, and Christoph Tillmann, IBM.)