15 search results - page 2 / 3 » Kernelization and Sparseness: the Case of Dominating Set |
SIAMSC
2008
13 years 5 months ago
2008
Abstract. This paper presents a new stochastic preconditioning approach for large sparse matrices. For the class of matrices that are row-wise and column-wise irreducibly diagonall...
JMLR
2012
11 years 7 months ago
2012
Sparse additive models are families of d-variate functions with the additive decomposition f∗ = ∑j∈S f∗ j , where S is an unknown subset of cardinality s d. In this paper,...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
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...
NIPS
2004
13 years 6 months ago
2004
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...
HVC
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. This paper studies the efficiency of several probabilistic model checkers by comparing verification times and peak memory usage for a set of standard case studies. The s...