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IPM
2006
151views more  IPM 2006»
14 years 10 months ago
Document clustering using nonnegative matrix factorization
A methodology for automatically identifying and clustering semantic features or topics in a heterogeneous text collection is presented. Textual data is encoded using a low rank no...
Farial Shahnaz, Michael W. Berry, V. Paul Pauca, R...
APWEB
2005
Springer
15 years 20 days ago
A Neural Network Approach to Web Graph Processing
In this paper, we will provide an overview of some of the more recent developments in web graph processing using the classic Google page rank equation as popularized by Brins and P...
Ah Chung Tsoi, Franco Scarselli, Marco Gori, Marku...
SIAMJO
2010
110views more  SIAMJO 2010»
14 years 5 months ago
Estimating Bounds for Quadratic Assignment Problems Associated with Hamming and Manhattan Distance Matrices Based on Semidefinit
Quadratic assignment problems (QAPs) with a Hamming distance matrix for a hypercube or a Manhattan distance matrix for a rectangular grid arise frequently from communications and ...
Hans D. Mittelmann, Jiming Peng
CORR
2011
Springer
157views Education» more  CORR 2011»
14 years 2 months ago
Large-Scale Convex Minimization with a Low-Rank Constraint
We address the problem of minimizing a convex function over the space of large matrices with low rank. While this optimization problem is hard in general, we propose an efficient...
Shai Shalev-Shwartz, Alon Gonen, Ohad Shamir
TSP
2008
103views more  TSP 2008»
14 years 10 months ago
Low-Rank Variance Approximation in GMRF Models: Single and Multiscale Approaches
Abstract--We present a versatile framework for tractable computation of approximate variances in large-scale Gaussian Markov random field estimation problems. In addition to its ef...
Dmitry M. Malioutov, Jason K. Johnson, Myung Jin C...