613 search results - page 102 / 123 » Learning the Structure of Linear Latent Variable Models |
ICONIP
2004
13 years 9 months ago
2004
Variational methods have proved popular and effective for inference and learning in intractable graphical models. An attractive feature of the approaches based on the Kullback-Lei...
MM
2004
ACM
14 years 29 days ago
2004
ACM
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
CIKM
2009
Springer
14 years 2 months ago
2009
Springer
Many applications in structure matching require the ability to search for graphs that are similar to a query graph, i.e., similarity graph queries. Prior works, especially in chem...
CORR
2010
Springer
13 years 6 months ago
2010
Springer
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
KDD
2009
ACM
14 years 8 months ago
2009
ACM
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...