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IJCNN
2008
IEEE
15 years 6 months ago
Sparse support vector machines trained in the reduced empirical feature space
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
Kazuki Iwamura, Shigeo Abe
PARLE
1994
15 years 4 months ago
Run-Time Optimization of Sparse Matrix-Vector Multiplication on SIMD Machines
Sparse matrix-vector multiplication forms the heart of iterative linear solvers used widely in scientific computations (e.g., finite element methods). In such solvers, the matrix-v...
Louis H. Ziantz, Can C. Özturan, Boleslaw K. ...
ICASSP
2010
IEEE
15 years 19 days ago
Sparse Bayesian step-filtering for high-throughput analysis of molecular machine dynamics
Nature has evolved many molecular machines such as kinesin, myosin, and the rotary flagellar motor powered by an ion current from the mitochondria. Direct observation of the step-...
Max A. Little, Nick S. Jones
114
Voted
CVPR
2005
IEEE
16 years 2 months ago
A Sparse Support Vector Machine Approach to Region-Based Image Categorization
Automatic image categorization using low-level features is a challenging research topic in computer vision. In this paper, we formulate the image categorization problem as a multi...
Jinbo Bi, Yixin Chen, James Ze Wang
TNN
2010
176views Management» more  TNN 2010»
14 years 7 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao