99 search results - page 14 / 20 » Learning Hidden Markov Models with Distributed State Represe... |
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...
ML
2000
ACM
13 years 7 months ago
2000
ACM
This paper discusses a novel distributed adaptive algorithm and representation used to construct populations of adaptive Web agents. These InfoSpiders browse networked information ...
CVPR
2012
IEEE
11 years 10 months ago
2012
IEEE
Modeling representations of image patches that are quasi-invariant to spatial deformations is an important problem in computer vision. In this paper, we propose a novel concept, t...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
This paper investigates the impact of subspace based techniques for acoustic modeling in automatic speech recognition (ASR). There are many well known approaches to subspace based...
TNN
1998
13 years 7 months ago
1998
—A structured organization of information is typically required by symbolic processing. On the other hand, most connectionist models assume that data are organized according to r...