4947 search results - page 240 / 990 » Learning Module Networks |
136
Voted
TNN
1998
15 years 3 months ago
1998
— This paper proposes two hierarchical schemes for learning, one for clustering and the other for classification problems. Both schemes can be implemented on a fuzzy lattice neu...
129
click to vote
IJAR
2010
15 years 1 months ago
2010
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...
172
Voted
BC
2002
15 years 3 months ago
2002
Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives...
128
Voted
PKDD
2010
Springer
15 years 1 months ago
2010
Springer
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
118
Voted
ICASSP
2009
IEEE
15 years 10 months ago
2009
IEEE
Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...