Special Seminar

Monday, May 22, 2017 - 1:00pm


ASA Conference Room 6115 Gates Hillman Centers


DAVID WOODRUFF, Research Staff Member http://researcher.watson.ibm.com/researcher/view.php?person=us-dpwoodru

We give an overview of near optimal algorithms for regression, low rank approximation, and robust variants of these problems. Our results are based on the sketch and solve paradigm, which is a tool for quickly compressing a problem to a smaller version of itself, for which one can then run a slow algorithm on the smaller problem. These lead to the fastest known algorithms for fundamental machine learning and numerical linear algebra problems, which run in time proportional to the number of non-zero entries of the input.—David Woodruff joined IBM Almaden Research Center in 2007 after completing his Ph.D. at MIT in theoretical computer science. His research interests include data stream algorithms, distributed algorithms, machine learning, numerical linear algebra, sketching, and sparse recovery. He is the recipient of the 2014 Presburger Award and Best Paper Awards at STOC 2013 and PODS 2010. At IBM he is a member of the Academy of Technology and a Master Inventor.Computer Science Department

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Special Seminar