561 search results - page 69 / 113 » Algorithms and applications for approximate nonnegative matr... |
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
IOR
2010
13 years 6 months ago
2010
We present exchange formulas that allow to express the stationary distribution of a continuous Markov chain with denumerable state-space having generator matrix Q∗ through a con...
CORR
2010
Springer
13 years 6 months ago
2010
Springer
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
ESA
2006
Springer
13 years 11 months ago
2006
Springer
An instance of the path hitting problem consists of two families of paths, D and H, in a common undirected graph, where each path in H is associated with a non-negative cost. We r...
ICCAD
2006
IEEE
14 years 4 months ago
2006
IEEE
Recent successful techniques for the efficient simulation of largescale interconnect models rely on the sparsification of the inverse of the inductance matrix L. While there are...