AND THE SOLUTION OF SYMMETRIC DIAGONALLY-DOMINANT LINEAR SYSTEMS Haesun Park College of Computing Georgia Institute / College Park / Wallenberg Hall / Computer Science Wake Forest University / Mathematics Massachusetts Institute of Technology / Modern Massive Datasets Stanford University / Mathematics University of Michigan / Advanced Computer Studies University of Maryland / Computer Science Yale University / Computer Science University of Maryland / Computer Science Rensselaer Polytechnic Institute / /
IndustryTerm
spectral imaging applications / Internet domain / medical imaging / updating and downdating algorithms / data mining / graph partitioning algorithm / numerical applications / nearly-linear time algorithms / spectral imaging / web search / internet recommendation systems / nearly-linear time algorithm / /
OperatingSystem
Petros / /
Organization
Wake Forest University / University of Michigan / Ann Arbor / Dianne O'Leary Department of Computer Science / Park College / Bob Plemmons Department of Mathematics / Santosh Vempala Department / Massachusetts Institute of Technology / Advanced Computer Studies University / University of Maryland / College Park / Yale University / Mathematics University / Ravi Kannan Department / Anna Gilbert/Martin Strauss Department / Rensselaer Polytechnic Institute / Stanford University / Computing Georgia Institute of Technology Motivated / G.W. Stewart Department / Petros Drineas Department / Daniel Spielman Department of Computer Science Yale University LOW-RANK NONNEGATIVE FACTORIZATIONS FOR SPECTRAL IMAGING APPLICATIONS / /
Workshop on Algorithms for Modern Massive Datasets Stanford University and Yahoo! Research The MMDS (modern massive datasets) workshop provides a forum for discussions on massive, high-dimensional, and