695 search results - page 14 / 139 » The structure of intrinsic complexity of learning |
ECAI
2004
Springer
14 years 27 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...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
ICPR
2008
IEEE
14 years 1 months ago
2008
IEEE
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
ICPR
2010
IEEE
13 years 5 months ago
2010
IEEE
In this paper, an easily implemented semi-supervised graph learning method is presented for dimensionality reduction and clustering, using the most of prior knowledge from limited...