The informative vector machine (IVM) is a practical method for Gaussian process regression and classification. The IVM produces a sparse approximation to a Gaussian process by com...
Neil D. Lawrence, John C. Platt, Michael I. Jordan
Background: Kernel-based classification and regression methods have been successfully applied to modelling a wide variety of biological data. The Kernel-based Orthogonal Projectio...
Background: Tight clustering arose recently from a desire to obtain tighter and potentially more informative clusters in gene expression studies. Scattered genes with relatively l...
Many impact studies require climate change information at a finer resolution than that provided by Global Climate Models (GCMs). In the last 10 years, downscaling techniques, both...
Masoud Hessami, Philippe Gachon, Taha B. M. J. Oua...
The maximum rank correlation (MRC) estimator was originally studied by Han [1987. Nonparametric analysis of a generalized regression model. J. Econometrics 35, 303–316] and Sher...