1845 search results - page 39 / 369 » Machine-Learning Applications of Algorithmic Randomness |
ICML
2004
IEEE
14 years 1 months ago
2004
IEEE
This paper describes an e cient method for learning the parameters of a Gaussian process (GP). The parameters are learned from multiple tasks which are assumed to have been drawn ...
ICML
2010
IEEE
13 years 9 months ago
2010
IEEE
Deep Belief Networks (DBNs) are hierarchical generative models which have been used successfully to model high dimensional visual data. However, they are not robust to common vari...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
COLT
2004
Springer
13 years 11 months ago
2004
Springer
We study the problem of classifying data in a given taxonomy when classifications associated with multiple and/or partial paths are allowed. We introduce an incremental algorithm u...
EMMCVPR
1999
Springer
14 years 8 days ago
1999
Springer
This paper considers the use of the EM-algorithm, combined with mean field theory, for parameter estimation in Markov random field models from unlabelled data. Special attention ...