Sciweavers

447 search results - page 37 / 90
» Choosing Multiple Parameters for Support Vector Machines
Sort
View
AUSAI
2008
Springer
13 years 9 months ago
Character Recognition Using Hierarchical Vector Quantization and Temporal Pooling
In recent years, there has been a cross-fertilization of ideas between computational neuroscience models of the operation of the neocortex and artificial intelligence models of mac...
John Thornton, Jolon Faichney, Michael Blumenstein...
ICMCS
2005
IEEE
94views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Event detection based on generic characteristics of field-sports
In this paper we propose a generic framework for event detection in broadcast video of multiple different field-sports. Features indicating significant events are selected, and ro...
David A. Sadlier, Noel E. O'Connor
ICML
2007
IEEE
14 years 8 months ago
More efficiency in multiple kernel learning
An efficient and general multiple kernel learning (MKL) algorithm has been recently proposed by Sonnenburg et al. (2006). This approach has opened new perspectives since it makes ...
Alain Rakotomamonjy, Francis Bach, Stéphane...
ICML
2005
IEEE
14 years 8 months ago
Supervised versus multiple instance learning: an empirical comparison
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Soumya Ray, Mark Craven
ICML
2004
IEEE
14 years 8 months ago
Multiple kernel learning, conic duality, and the SMO algorithm
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
Francis R. Bach, Gert R. G. Lanckriet, Michael I. ...