Scientific Computing and Matrix Computations Seminar

Organized by James Demmel and Ming Gu

Spring 2010

Wednesdays 11:00AM-Noon in 380 Soda Hall.


Past Seminars

Current Schedule


Date Speaker Affiliation Talk
Jan. 20 Oded Schwartz
Technische Universitat Berlin
Expanders and Communication-Avoiding Algorithms. Meeting in 740 Evans.
Jan. 27 Mark Hoemmen
UC Berkeley
Communication-avoiding Krylov subspace methods (Dissertation Talk) . Slides Available.
Feb. 3 Prof. W. Kahan
UC Berkeley
Tutorial: How to Compute Real Cube Roots Well
Feb. 10
Panayot Vassilevski
Lawrence Livermore National Lab
Multigrid and Algebraic multigrid: main principles, definitions, algorithms and applications (Part I) with slides. Joint with LBNL Computing Sciencces Seminar .
Feb. 17
Panayot Vassilevski
Lawrence Livermore National Lab
Multigrid and Algebraic multigrid: main principles, definitions, algorithms and applications (Part II) . Joint with LBNL Computing Sciencces Seminar .
Feb. 24
Zhenhai Zhu
Cadence Research Labs
A Parameterized Mask Model for Lithography Simulation . More details.
March 3
Prof. Emmanuel Candes
Stanford University
Robust Principal Component Analysis? Joint EECS Colloquium, refreshments 3:30-4:00PM in Wozniak Lounge. Talk at 306 Soda at 4:00PM.
March 10
Dr. Paul Constantine
Sandia National Lab
Computational Methods for Parameterized Matrix Equations Slides available.
March 17
Avi Robinson-Mosher
Stanford University
A symmetric positive definite method for fluid-structure interaction. Slides available in power point.
March 24
No Seminar.

Spring Break
March 31
Dr. Ken Clarkson
IBM Almaden Research
Numerical Linear Algebra in the Streaming Model
April 7
Prof. Gil Strang
MIT
The Algebra of Fast Transforms: Banded Matrices with Banded Inverses
April 14
Prof. James O'Brien
UC Berkeley
Mesh Modification and Real-Time FEM Simulation
April 21
Prof. Joel Tropp
CalTech
Finding structure with randomness: Stochastic algorithms for constructing low-rank matrix decompositions
April 28
Ewout van den Berg
Stanford University
Sparse optimization with least-squares constraints