369 search results - page 26 / 74 » Layered Learning |
JMLR
2010
13 years 2 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
PAM
2005
Springer
14 years 1 months ago
2005
Springer
A number of key areas in IP network engineering, management and surveillance greatly benefit from the ability to dynamically identify traffic flows according to the applications re...
ECAI
2004
Springer
14 years 29 days ago
2004
Springer
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
NIPS
2007
13 years 9 months ago
2007
We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
EDM
2010
13 years 9 months ago
2010
It is argued that the analysis of the learner's generated log files during interactions with a learning environment is necessary to produce interpretative views of their activ...