68 search results - page 5 / 14 » Inductive Principles for Restricted Boltzmann Machine Learni... |
AAAI
2011
12 years 7 months ago
2011
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
IJCNN
2006
IEEE
14 years 1 months ago
2006
IEEE
— We have found a more general formulation of the REINFORCE learning principle which had been proposed by R. J. Williams for the case of artificial neural networks with stochast...
IJCV
2000
13 years 7 months ago
2000
In this paper we first overview the main concepts of Statistical Learning Theory, a framework in which learning from examples can be studied in a principled way. We then briefly di...
COLING
2010
13 years 2 months ago
2010
This paper presents a novel semisupervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification problem with active learni...
UAI
1996
13 years 9 months ago
1996
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...