2914 search results - page 68 / 583 » Learning and Inference with Constraints |
CP
2009
Springer
14 years 8 months ago
2009
Springer
In constraint satisfaction, basic inferences rely on some properties of constraint networks, called consistencies, that allow the identification of inconsistent instantiations (als...
SSPR
2004
Springer
14 years 1 months ago
2004
Springer
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
COLT
2004
Springer
14 years 1 months ago
2004
Springer
We define the problem of inferring a “mixture of Markov chains” based on observing a stream of interleaved outputs from these chains. We show a sharp characterization of the i...
NIPS
2003
13 years 9 months ago
2003
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to sem...
GLOBECOM
2010
IEEE
13 years 5 months ago
2010
IEEE
Cognitive networking deals with applying cognition to the entire network protocol stack for achieving stack-wide as well as network-wide performance goals, unlike cognitive radios ...