This paper presents a new method for the selection of the two hyperparameters of Least Squares Support Vector Machine (LS-SVM) approximators with Gaussian Kernels. The two hyperpar...
Amaury Lendasse, Yongnan Ji, Nima Reyhani, Michel ...
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
Asma Rabaoui, Nicolas Viandier, Juliette Marais, E...
In this paper we present a new sparse iterative covariance-based estimation approach, called SPICE, to the direction of arrival estimation problem. SPICE is obtained by the minimi...
Quantile regression refers to the process of estimating the quantiles of a conditional distribution and has many important applications within econometrics and data mining, among ...
Novi Quadrianto, Kristian Kersting, Mark D. Reid, ...
In this paper, a global methodology for the long-term prediction of time series is proposed. This methodology combines direct prediction strategy and sophisticated input selection...
Antti Sorjamaa, Jin Hao, Nima Reyhani, Yongnan Ji,...