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ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
14 years 3 months ago
Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
Ramesh Natarajan, Vikas Sindhwani, Shirish Tatikon...
ICS
2005
Tsinghua U.
14 years 2 months ago
Parallel sparse LU factorization on second-class message passing platforms
Several message passing-based parallel solvers have been developed for general (non-symmetric) sparse LU factorization with partial pivoting. Due to the fine-grain synchronizatio...
Kai Shen
SIAMNUM
2010
134views more  SIAMNUM 2010»
13 years 3 months ago
Nonequispaced Hyperbolic Cross Fast Fourier Transform
A straightforward discretisation of problems in d spatial dimensions often leads to an exponential growth in the number of degrees of freedom. Thus, even efficient algorithms like ...
Michael Döhler, Stefan Kunis, Daniel Potts
KDD
1998
ACM
147views Data Mining» more  KDD 1998»
14 years 23 days ago
ADtrees for Fast Counting and for Fast Learning of Association Rules
Abstract: The problem of discovering association rules in large databases has received considerable research attention. Much research has examined the exhaustive discovery of all a...
Brigham S. Anderson, Andrew W. Moore
CISS
2008
IEEE
14 years 3 months ago
Distributed processing in frames for sparse approximation
—Beyond signal processing applications, frames are also powerful tools for modeling the sensing and information processing of many biological and man-made systems that exhibit in...
Christopher J. Rozell