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TRECVID
2008
13 years 8 months ago
ISM TRECVID2008 High-level Feature Extraction
We studied a method using support vector machines (SVMs) with walk-based graph kernels for the high-level feature extraction (HLF) task. In this method, each image is first segmen...
Tomoko Matsui, Jean-Philippe Vert, Shin'ichi Satoh...
ICASSP
2009
IEEE
13 years 11 months ago
High-level feature extraction using SVM with walk-based graph kernel
We investigate a method using support vector machines (SVMs) with walk-based graph kernels for high-level feature extraction from images. In this method, each image is first segme...
Jean-Philippe Vert, Tomoko Matsui, Shin'ichi Satoh...
ICML
2006
IEEE
14 years 8 months ago
On a theory of learning with similarity functions
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Maria-Florina Balcan, Avrim Blum
JMLR
2006
124views more  JMLR 2006»
13 years 7 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...
ML
2008
ACM
110views Machine Learning» more  ML 2008»
13 years 5 months ago
A theory of learning with similarity functions
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Maria-Florina Balcan, Avrim Blum, Nathan Srebro