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PKDD
2010
Springer
169views Data Mining» more  PKDD 2010»
13 years 7 months ago
Efficient and Numerically Stable Sparse Learning
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
Sihong Xie, Wei Fan, Olivier Verscheure, Jiangtao ...
BMCBI
2008
171views more  BMCBI 2008»
13 years 10 months ago
A general approach to simultaneous model fitting and variable elimination in response models for biological data with many more
Background: With the advent of high throughput biotechnology data acquisition platforms such as micro arrays, SNP chips and mass spectrometers, data sets with many more variables ...
Harri T. Kiiveri
EUROPAR
2004
Springer
14 years 3 months ago
Task-Queue Based Hybrid Parallelism: A Case Study
Abstract. In this paper we report on our experiences with hybrid parallelism in PARDISO, a high-performance sparse linear solver. We start with the OpenMP-parallel numerical factor...
Karl Fürlinger, Olaf Schenk, Michael Hagemann
PAAPP
2002
150views more  PAAPP 2002»
13 years 9 months ago
Scalability analysis of parallel GMRES implementations
Applications involving large sparse nonsymmetric linear systems encourage parallel implementations of robust iterative solution methods, such as GMRES(k). Two parallel versions of...
Masha Sosonkina, Donald C. S. Allison, Layne T. Wa...
CORR
2008
Springer
129views Education» more  CORR 2008»
13 years 10 months ago
Polynomial Linear Programming with Gaussian Belief Propagation
Abstract--Interior-point methods are state-of-the-art algorithms for solving linear programming (LP) problems with polynomial complexity. Specifically, the Karmarkar algorithm typi...
Danny Bickson, Yoav Tock, Ori Shental, Danny Dolev