319 search results - page 21 / 64 » Learning Nonlinear Manifolds from Time Series |
PAMI
2002
14 years 9 months ago
2002
We investigate the use of linear and nonlinear principal manifolds for learning low-dimensional representations for visual recognition. Several leading techniques: Principal Compo...
74
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JMLR
2010
14 years 4 months ago
2010
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
73
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IJCAI
2007
14 years 11 months ago
2007
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
100
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SIGPRO
2008
14 years 9 months ago
2008
This paper introduces a novel method for real-time estimation of slowly varying parameters in nonlinear dynamical systems. The core concept is built upon the principles of symboli...
CEC
2009
IEEE
15 years 4 months ago
2009
IEEE
— The paper proposes a hypernetwork-based method for stock market prediction through a binary time series problem. Hypernetworks are a random hypergraph structure of higher-order...