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KSEM
2009
Springer
15 years 8 months ago
A Competitive Learning Approach to Instance Selection for Support Vector Machines
Abstract. Support Vector Machines (SVM) have been applied successfully in a wide variety of fields in the last decade. The SVM problem is formulated as a convex objective function...
Mario Zechner, Michael Granitzer
SAGA
2009
Springer
15 years 8 months ago
Bounds for Multistage Stochastic Programs Using Supervised Learning Strategies
We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible dec...
Boris Defourny, Damien Ernst, Louis Wehenkel
CVPR
2003
IEEE
16 years 3 months ago
Learning Affinity Functions for Image Segmentation: Combining Patch-based and Gradient-based Approaches
This paper studies the problem of combining region and boundary cues for natural image segmentation. We employ a large database of manually segmented images in order to learn an o...
Charless Fowlkes, David R. Martin, Jitendra Malik
ICCV
2007
IEEE
16 years 3 months ago
Learning 3-D Scene Structure from a Single Still Image
We consider the problem of estimating detailed 3-d structure from a single still image of an unstructured environment. Our goal is to create 3-d models which are both quantitative...
Ashutosh Saxena, Min Sun, Andrew Y. Ng
ICPR
2008
IEEE
16 years 2 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...