68 search results - page 7 / 14 » Inductive Principles for Restricted Boltzmann Machine Learni... |
ECCV
2010
Springer
14 years 29 days ago
2010
Springer
Abstract. We address the problem of learning good features for understanding video data. We introduce a model that learns latent representations of image sequences from pairs of su...
NIPS
2007
13 years 9 months ago
2007
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
ILP
2003
Springer
14 years 24 days ago
2003
Springer
The learning system Progol5 and the underlying inference method of Bottom Generalisation are firmly established within Inductive Logic Programming (ILP). But despite their success...
ICML
2009
IEEE
14 years 2 months ago
2009
IEEE
The most commonly used learning algorithm for restricted Boltzmann machines is contrastive divergence which starts a Markov chain at a data point and runs the chain for only a few...
JMLR
2010
13 years 2 months ago
2010
Contrastive Divergence (CD) is a popular method for estimating the parameters of Markov Random Fields (MRFs) by rapidly approximating an intractable term in the gradient of the lo...