259 search results - page 28 / 52 » A Hybrid Convergent Method for Learning Probabilistic Networ... |
AAAI
2010
13 years 9 months ago
2010
Many problems require repeated inference on probabilistic graphical models, with different values for evidence variables or other changes. Examples of such problems include utilit...
CORR
2010
Springer
13 years 6 months ago
2010
Springer
Structured output prediction is an important machine learning problem both in theory and practice, and the max-margin Markov network (M3 N) is an effective approach. All state-of-...
SAGA
2007
Springer
14 years 1 months ago
2007
Springer
We consider applications of probabilistic techniques in the framework of algorithmic game theory. We focus on three distinct case studies: (i) The exploitation of the probabilistic...
IJCAI
1997
13 years 9 months ago
1997
We study the problemof statisticallycorrect inference in networks whose basic representations are population codes. Population codes are ubiquitous in the brain, and involve the s...
IJON
2002
13 years 7 months ago
2002
This paper presents a new adaptive procedure for the linear and non-linear separation of signals with non-uniform, symmetrical probability distributions, based on both simulated a...