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ICML
2008
IEEE
14 years 8 months ago
Composite kernel learning
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Mul...
Marie Szafranski, Yves Grandvalet, Alain Rakotomam...
ISCAS
2002
IEEE
125views Hardware» more  ISCAS 2002»
14 years 10 days ago
Switching activity estimation of finite state machines for low power synthesis
A technique for computing the switching activity of synchronous Finite State Machine (FSM) implementations including the influence of temporal correlation among the next state si...
Mikael Kerttu, Per Lindgren, Mitchell A. Thornton,...
ICCV
2007
IEEE
14 years 1 months ago
Learning The Discriminative Power-Invariance Trade-Off
We investigate the problem of learning optimal descriptors for a given classification task. Many hand-crafted descriptors have been proposed in the literature for measuring visua...
Manik Varma, Debajyoti Ray
ICCV
2001
IEEE
14 years 9 months ago
JetStream: Probabilistic Contour Extraction with Particles
The problem of extracting continuous structures from noisy or cluttered images is a difficult one. Successful extraction depends critically on the ability to balance prior constra...
Andrew Blake, Michel Gangnet, Patrick Pérez
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
14 years 7 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...