Yoram Singer : 2013 Plenary Session

We review the design, analysis and implementation of a few machine learning algorithms for learning from high-dimensional and large amounts of data. We focus on algorithms that are both efficient and can yield compact models. Examples of projects at Google that use these algorithms will be given.

Yoram Singer is a senior research scientist at Google. From 1999 through 2007 he was an associate professor at the Hebrew University of Jerusalem. From 1995 through 1999 he was a member of the technical staff at AT&T Research. He was the co-chair of the conference on Computational Learning Theory in 2004 and of Neural Information Processing Systems in 2007. He serves as an editor of the Journal of Machine Learning and IEEE Signal Processing Magazine.