A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
—We present an application of machine learning to the semi-automatic synthesis of robust servo-trackers for underwater robotics. In particular, we investigate an approach based o...
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
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...
Violations of functional dependencies (FDs) are common in practice, often arising in the context of data integration or Web data extraction. Resolving these violations is known to...