10 search results - page 2 / 2 » Learning Markov networks: maximum bounded tree-width graphs |
NIPS
2003
13 years 6 months ago
2003
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
ALT
2010
Springer
13 years 6 months ago
2010
Springer
We consider the problem of inferring the most likely social network given connectivity constraints imposed by observations of outbreaks within the network. Given a set of vertices ...
NN
1997
Springer
13 years 8 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
ICDAR
2007
IEEE
13 years 11 months ago
2007
IEEE
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
ICML
1996
IEEE
14 years 5 months ago
1996
IEEE
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...