1704 search results - page 92 / 341 » Learning nonlinear dynamic models |
130
click to vote
JMLR
2010
14 years 7 months ago
2010
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
121
Voted
CVPR
2003
IEEE
16 years 2 months ago
2003
IEEE
This paper addresses the problem of capturing the dynamics for exemplar-based recognition systems. Traditional HMM provides a probabilistic tool to capture system dynamics and in ...
115
Voted
SDM
2012
SIAM
13 years 3 months ago
2012
SIAM
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
111
Voted
CIIA
2009
15 years 1 months ago
2009
Petroleum industry production systems are highly automatized. In this industry, all functions (e.g., planning, scheduling and maintenance) are automated and in order to remain comp...
124
click to vote
TNN
1998
15 years 13 days ago
1998
—Structural learning with forgetting is an established method of using Laplace regularization to generate skeletal artificial neural networks. In this paper we develop a continu...