259 search results - page 35 / 52 » A Hybrid Convergent Method for Learning Probabilistic Networ... |
AMAI
2004
Springer
14 years 1 months ago
2004
Springer
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
JSAC
2010
13 years 6 months ago
2010
—Inspired by the biological entities’ ability to achieve reciprocity in the course of evolution, this paper considers a conjecture-based distributed learning approach that enab...
TVLSI
2010
13 years 2 months ago
2010
Clock network is a vulnerable victim of variations as well as a main power consumer in many integrated circuits. Recently, link-based non-tree clock network attracts people's...
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
— A solution for the slow convergence of most learning rules for Recurrent Neural Networks (RNN) has been proposed under the terms Liquid State Machines (LSM) and Echo State Netw...
UAI
2000
13 years 9 months ago
2000
In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different c...