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Title |
Fast Monte Carlo Algorithms for Matrix Operations and Massive
Data Set Analysis
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| Speaker |
Michael W. Mahoney
Department of Mathematics
Yale University
michael.mahoney@yale.edu
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| Date |
September 16, 2004 |
| Time |
10-11am (PT)
11am-noon (MT)
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| Location |
921/137 (CA)
980/24 (NM)
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| 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.
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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.
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| Host |
Tamara G. Kolda, tgkolda@sandia.gov, 925-294-4769
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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. In this
case, 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 Building 911 (this access is
valid for a period of one year).
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