The stochastic approximation method is behind the solution to many important, actively-studied problems in machine learning. Despite its farreaching application, there is almost n...
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
Segmentation of range images has long been considered an important and difficult problem and continues to attract the attention of researchers in computer vision. In this paper we...
: Global Navigation Satellite Systems (GNSS) are often used to localise a receiver with respect to a given map. This association problem, also known as map-matching, is usually add...
This paper addresses the problem of variable ranking for Support Vector Regression. The relevance criteria that we proposed are based on leave-one-out bounds and some variants and...