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» The Structure of Sparse Resultant Matrices
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181
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ICML
2005
IEEE
16 years 4 months ago
Analysis and extension of spectral methods for nonlinear dimensionality reduction
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
Fei Sha, Lawrence K. Saul
127
Voted
ICDM
2009
IEEE
174views Data Mining» more  ICDM 2009»
15 years 10 months ago
Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis
—We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...
Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muha...
147
Voted
IPPS
2003
IEEE
15 years 9 months ago
Parallel Direct Solution of Linear Equations on FPGA-Based Machines
The efficient solution of large systems of linear equations represented by sparse matrices appears in many tasks. LU factorization followed by backward and forward substitutions i...
Xiaofang Wang, Sotirios G. Ziavras
132
Voted
LSSC
2001
Springer
15 years 8 months ago
Solving Systems of Linear Algebraic Equations Using Quasirandom Numbers
In this paper we analyze a quasi-Monte Carlo method for solving systems of linear algebraic equations. It is well known that the convergence of Monte Carlo methods for numerical in...
Aneta Karaivanova, Rayna Georgieva
141
Voted
ICA
2007
Springer
15 years 5 months ago
Gradient Convolution Kernel Compensation Applied to Surface Electromyograms
Abstract. This paper introduces gradient based method for robust assessment of the sparse pulse sources, such as motor unit innervation pulse trains in the filed of electromyograp...
Ales Holobar, Damjan Zazula