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DATE
2004
IEEE
108views Hardware» more  DATE 2004»
15 years 6 months ago
Poor Man's TBR: A Simple Model Reduction Scheme
This paper presents a model reduction algorithm motivated by a connection between frequency domain projection methods and approximation of truncated balanced realizations. The met...
Joel R. Phillips, Luis Miguel Silveira
JMLR
2010
103views more  JMLR 2010»
14 years 10 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
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...
Tzu-Kuo Huang, Le Song, Jeff Schneider
ECML
2005
Springer
15 years 8 months ago
Inducing Hidden Markov Models to Model Long-Term Dependencies
We propose in this paper a novel approach to the induction of the structure of Hidden Markov Models. The induced model is seen as a lumped process of a Markov chain. It is construc...
Jérôme Callut, Pierre Dupont
ICIP
2007
IEEE
15 years 7 months ago
Unsupervised Nonlinear Manifold Learning
This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
Matthieu Brucher, Christian Heinrich, Fabrice Heit...
AUTOMATICA
2011
14 years 10 months ago
Sequential linear quadratic control of bilinear parabolic PDEs based on POD model reduction
We present a framework to solve a finite-time optimal control problem for parabolic partial differential equations (PDEs) with diffusivity-interior actuators, which is motivate...
Chao Xu, Yongsheng Ou, Eugenio Schuster