319 search results - page 26 / 64 » Learning Nonlinear Manifolds from Time Series |
80
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NIPS
2004
14 years 11 months ago
2004
We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regulariza...
106
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KDD
2009
ACM
15 years 2 months ago
2009
ACM
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
COMPGEOM
2010
ACM
15 years 1 months ago
2010
ACM
We give a provably correct algorithm to reconstruct a kdimensional manifold embedded in d-dimensional Euclidean space. Input to our algorithm is a point sample coming from an unkn...
ESANN
2008
14 years 11 months ago
2008
This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental ...
ICANN
2009
Springer
15 years 2 months ago
2009
Springer
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...