Least Squares Support Vector Machines for Kernel CCA in Nonlinear State-Space Identification

By Vincent Verdult, Johan A. K. Suykens, Jeroen Boets, Ivan Goethals, B. De Moor. 2004

21 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Jonathan Ko
2. Dieter Fox
3. Marc Peter Deisenroth
4. Yoshinobu Kawahara
5. Takehisa Yairi
6. K. Machida
7. Sergey Levine
8. Carl E. Rasmussen

Citations in the corpus

• Learning GP-BayesFilters via Gaussian process latent variable models (2009, background): “The system we wish to model is the small problem presented in Kawahara et al. (2007) and Verdult et al. (2004).”
• A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems (2006, methodology): “have been proposed to date include only those in which models w ith specific nonlinearities are assumed [6] or those which need complicated nonlinear regression [7,8].”