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DATE
2004
IEEE
108views Hardware» more  DATE 2004»
14 years 22 days 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»
13 years 3 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
14 years 2 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
14 years 26 days 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
13 years 4 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