343 search results - page 9 / 69 » Imitation Learning Using Graphical Models |
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
The supremacy of n-gram models in statistical language modelling has recently been challenged by parametric models that use distributed representations to counteract the difficult...
IPM
2008
13 years 9 months ago
2008
This article explores how to develop complex data driven user models that go beyond the bag of words model and topical relevance. We propose to learn from rich user specific info...
TSP
2010
13 years 4 months ago
2010
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
JMLR
2010
13 years 4 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...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
This paper investigates compression of 3D objects in computer graphics using manifold learning. Spectral compression uses the eigenvectors of the graph Laplacian of an object'...