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» A subdivision-based algorithm for the sparse resultant
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ICML
2009
IEEE
16 years 2 months ago
Sparse Gaussian graphical models with unknown block structure
Recent work has shown that one can learn the structure of Gaussian Graphical Models by imposing an L1 penalty on the precision matrix, and then using efficient convex optimization...
Benjamin M. Marlin, Kevin P. Murphy
ICML
2008
IEEE
16 years 2 months ago
Sparse multiscale gaussian process regression
Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
Bernhard Schölkopf, Christian Walder, Kwang I...
IPPS
2000
IEEE
15 years 5 months ago
Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems
Abstract. Computer simulations of realistic applications usually require solving a set of non-linear partial di erential equations PDEs over a nite region. The process of obtaini...
Leonid Oliker, Xiaoye S. Li, Gerd Heber, Rupak Bis...
EUROPAR
1998
Springer
15 years 5 months ago
Parallel Sparse Matrix Computations Using the PINEAPL Library: A Performance Study
Abstract. The Numerical Algorithms Group Ltd is currently participating in the European HPCN Fourth Framework project on Parallel Industrial NumErical Applications and Portable Lib...
Arnold R. Krommer
ICML
2010
IEEE
15 years 2 months ago
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
Mingkui Tan, Li Wang, Ivor W. Tsang