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STOC
2001
ACM
138views Algorithms» more  STOC 2001»
14 years 8 months ago
Fast computation of low rank matrix
Given a matrix A, it is often desirable to find a good approximation to A that has low rank. We introduce a simple technique for accelerating the computation of such approximation...
Dimitris Achlioptas, Frank McSherry
CVPR
2007
IEEE
14 years 9 months ago
Optimizing Distribution-based Matching by Random Subsampling
We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probabili...
Alex Po Leung, Shaogang Gong
ICDM
2006
IEEE
296views Data Mining» more  ICDM 2006»
14 years 1 months ago
Fast Random Walk with Restart and Its Applications
How closely related are two nodes in a graph? How to compute this score quickly, on huge, disk-resident, real graphs? Random walk with restart (RWR) provides a good relevance scor...
Hanghang Tong, Christos Faloutsos, Jia-Yu Pan
DISCO
1993
114views Hardware» more  DISCO 1993»
13 years 11 months ago
Gauss: A Parameterized Domain of Computation System with Support for Signature Functions
The fastest known algorithms in classical algebra make use of signature functions. That is, reducing computation with formulae to computing with the integers modulo p, by substitut...
Michael B. Monagan
AAAI
2011
12 years 7 months ago
Fast Newton-CG Method for Batch Learning of Conditional Random Fields
We propose a fast batch learning method for linearchain Conditional Random Fields (CRFs) based on Newton-CG methods. Newton-CG methods are a variant of Newton method for high-dime...
Yuta Tsuboi, Yuya Unno, Hisashi Kashima, Naoaki Ok...