From mmarti7 at sandia.gov Thu Sep 2 15:49:41 2004 From: mmarti7 at sandia.gov (Martinez-Canales, Monica L) Date: Mon Oct 23 09:14:12 2006 Subject: [CSRI/CSMR Seminars] First Announcement: Talk by Prof. Mahoney on 9/16 Message-ID: The Computer Science Research Institute Seminar Series presents.... Fast Monte Carlo Algorithms for Matrix Operations and Massive Data Set Analysis Michael W. Mahoney Department of Mathematics Yale University September 16, 2004 10-11am(PT) / 921/137 (CA) 11am-noon (MT) / 980/24 (NM) Abstract: We are interested in developing and analyzing fast Monte Carlo algorithms for performing useful computations on large matrices. Examples of such computations include matrix multiplication, the computation of the Singular Value Decomposition of a matrix, the computation of the compressed approximate CUR decomposition of a matrix, and testing the feasibility or infeasibility of a linear program. We present a Pass-Efficient model of data streaming computation in which our algorithms may naturally be formulated and present algorithms that are efficient within this model for each of the four types of matrix operations mentioned previously. We then describe how extensions of the CUR decomposition may be used for improved kernel-based statistical learning and for the efficient approximation of massive tensor-based data sets. This is joint work with Petros Drineas and Ravi Kannan. POC/Host: Tamara G. Kolda, tgkolda@sandia.gov, 925-294-4769 ---------------------------------------------------------------------------- ------------------------------- This seminar series is hosted by the Computational Sciences and Mathematics Research Department at Sandia National Labs in Livermore, CA. This seminar is funded by the Computer Science Research Institute (CSRI). To schedule a time to meet with the speaker before or after the talk, please make arrangements with the host listed above. Visitors from outside Sandia require at least 3 days notice in order to attend. For more information, see http://csmr.ca.sandia.gov/csri/visitor.html . The exception is any U.S. Citizens with a valid DOE badge. Have the badge activated for CA site access by going to the badge office in buidling 911. -------------- next part -------------- An HTML attachment was scrubbed... URL: http://csmr.ca.sandia.gov/pipermail/csri_seminars/attachments/20040902/b7534b0a/attachment.html From mmarti7 at sandia.gov Mon Sep 13 17:01:33 2004 From: mmarti7 at sandia.gov (Martinez-Canales, Monica L) Date: Mon Oct 23 09:14:12 2006 Subject: [CSRI/CSMR Seminars] Second Announcement: Talk by Prof. Mahoney on 9/16/2004 Message-ID: <284C755D981EB84F93CF602904340BEB0685B5@ES20SNLNT.srn.sandia.gov> The Computer Science Research Institute Seminar Series presents.... Fast Monte Carlo Algorithms for Matrix Operations and Massive Data Set Analysis by Michael W. Mahoney Department of Mathematics Yale University michael.mahoney@yale.edu September 16, 2004 10-11am (PT) / 11am-noon (MT) Bldg. 921, Rm. 137 (CA) / Bldg. 980, Rm. 24 (NM) Abstract: We are interested in developing and analyzing fast Monte Carlo algorithms for performing useful computations on large matrices. Examples of such computations include matrix multiplication, the computation of the Singular Value Decomposition of a matrix, the computation of the compressed approximate CUR decomposition of a matrix, and testing the feasibility or infeasibility of a linear program. We present a Pass-Efficient model of data streaming computation in which our algorithms may naturally be formulated and present algorithms that are efficient within this model for each of the four types of matrix operations mentioned previously. We then describe how extensions of the CUR decomposition may be used for improved kernel-based statistical learning and for the efficient approximation of massive tensor-based data sets. This is joint work with Petros Drineas and Ravi Kannan. About the Speaker: Michael W. Mahoney is currently a J. W. Gibbs Assistant Professor in the Department of Mathematics and a Research Affiliate in the Department of Computer Science at Yale University. His research interests include applied mathematics and theoretical computer science, and the application of these methods to problems in physics, chemistry, and biology involving large data sets. For example, recent work has involved the design and mathematical analysis of randomized algorithms for extremely large linear algebra problems, and the application of these algorithmic methods to the identification and extraction of structure in extremely large chemical and biological data sets. He received his Ph.D. from the Department of Physics at Yale University with a dissertation in computational liquid state statistical mechanics. Host/POC: Tamara G. Kolda, tgkolda@sandia.gov, 925-294-4769 --------------------------------------------------------------------- This seminar series is hosted by the Computational Sciences and Mathematics Research Department at Sandia National Labs in Livermore, CA. This seminar is funded by the Computer Science Research Institute (CSRI). To schedule a time to meet with the speaker before or after the talk, please make arrangements with the host listed above. Visitors from outside Sandia require at least 3 days notice in order to attend. For more information, see http://csmr.ca.sandia.gov/csri/visitor.html. For visitors that are U.S. Citizens with a valid DOE badge, please call for "key service" using the phone at the turnstile in front of Building 921. Alternatively, have the badge activated for site access by going to the badge office in buidling 911. -------------- next part -------------- An HTML attachment was scrubbed... URL: http://csmr.ca.sandia.gov/pipermail/csri_seminars/attachments/20040913/7b163528/attachment.html