The next lecture in the Helsinki Distinguished Lecture Series on Future Information Technology will be given by Head of Google Research, New York, Corinna Cortes.

The lecture will be followed by cocktails.

The event is free of charge and open to all interested in the leading research in information technology.

Please register at https://elomake.helsinki.fi/lomakkeet/47659/lomake.html by Wednesday 8 January, 2014.

Searching for Similar Items in Diverse Universes

Abstract

Google's diverse and ever-growing search domains present new challenges to machine learning. They require designing effective similarity measures that are efficient to compute. In this talk, I will discuss several algorithmic advances and implementation solutions we have designed at Google to handle some of these problems for metric spaces as well as graph-based representations.

The talk will discuss machine learning examples from a number of Google applications including Image, YouTube, and Structured Data Search.

Biography

Corinna Cortes is the Head of Google Research, NY, where she is working on a broad range of theoretical and applied large-scale machine learning problems. Prior to Google, Corinna spent more than ten years at AT&T Labs - Research, formerly AT&T Bell Labs, where she held a distinguished research position. Corinna's research work is well-known in particular for her contributions to the theoretical foundations of support vector machines (SVMs), for which she jointly with Vladimir Vapnik received the 2008 Paris Kanellakis Theory and Practice Award, and her work on data-mining in very large data sets for which she was awarded the AT&T Science and Technology Medal in the year 2000. Corinna received her MS degree in Physics from University of Copenhagen and joined AT&T Bell Labs as a researcher in 1989. She received her Ph.D. in computer science from the University of Rochester in 1993.