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Seminar abstract

Greedy Algorithms for Sparse Learning

Tong Zhang
Rutgers University

Abstract :

Sparse Learning has attracted much attention in recent years. There are two classes of methods: convex relaxation such as L1 regularization and greedy algorithms. Although the former has received more attention in the machine learning community, my opinion is that the latter approach is more flexible and powerful. This talk will discuss variations of greedy algorithms in the context of sparse recovery.


Tong Zhang received a B.A. in mathematics and computer science from Cornell University in 1994 and a Ph.D. in Computer Science from Stanford University in 1998. After graduation, he worked at IBM T.J. Watson Research Center in Yorktown Heights, New York, and Yahoo Research in New York city. He is currently a statistics professor at Rutgers University. His research interests include machine learning, algorithms for statistical computation, their mathematical analysis and applications.
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