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: <AC89BDA1E3CCBC42B9CA5B50FE7934D305ED4EC2@es10snlnt.sandia.gov>

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
<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.

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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.

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