23 search results - page 4 / 5 » Learning and Approximation of Chaotic Time Series Using Wave... |
NN
1997
Springer
13 years 10 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
NN
2000
Springer
13 years 5 months ago
2000
Springer
Piecewise-linear (PWL) neural networks are widely known for their amenability to digital implementation. This paper presents a new algorithm for learning in PWL networks consistin...
KDD
2008
ACM
14 years 6 months ago
2008
ACM
Multi-core processors with ever increasing number of cores per chip are becoming prevalent in modern parallel computing. Our goal is to make use of the multi-core as well as multi...
ICML
2004
IEEE
14 years 6 months ago
2004
IEEE
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...