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» Sparse Recovery Using Sparse Random Matrices
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ISNN
2007
Springer
15 years 4 months ago
A Hierarchical Self-organizing Associative Memory for Machine Learning
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
Janusz A. Starzyk, Haibo He, Yue Li
IPPS
2003
IEEE
15 years 3 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
NIPS
2007
14 years 11 months ago
Continuous Time Particle Filtering for fMRI
We construct a biologically motivated stochastic differential model of the neural and hemodynamic activity underlying the observed Blood Oxygen Level Dependent (BOLD) signal in Fu...
Lawrence Murray, Amos J. Storkey
NIPS
2004
14 years 11 months ago
Computing regularization paths for learning multiple kernels
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
MST
2010
98views more  MST 2010»
14 years 8 months ago
Why Almost All k-Colorable Graphs Are Easy to Color
Coloring a k-colorable graph using k colors (k ≥ 3) is a notoriously hard problem. Considering average case analysis allows for better results. In this work we consider the unif...
Amin Coja-Oghlan, Michael Krivelevich, Dan Vilench...