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NIPS
2008
15 years 8 months ago
An interior-point stochastic approximation method and an L1-regularized delta rule
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...
Peter Carbonetto, Mark Schmidt, Nando de Freitas
NIPS
2004
15 years 8 months ago
Computing regularization paths for learning multiple kernels
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
VMV
2001
86views Visualization» more  VMV 2001»
15 years 8 months ago
Segmentation of Range Images through the Integration of Different Strate Gies
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...
Mary Ellen Bock, Concettina Guerra
IJIIDS
2008
95views more  IJIIDS 2008»
15 years 7 months ago
Tightly-coupled GIS data in GNSS fix computations with integrity testing
: 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...
Clément Fouque, Philippe Bonnifait
IJON
2007
134views more  IJON 2007»
15 years 7 months ago
Analysis of SVM regression bounds for variable ranking
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...
Alain Rakotomamonjy