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» Kernels and Regularization on Graphs
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106
Voted
ICPR
2008
IEEE
15 years 7 months ago
Regularized discriminant analysis for transformation-invariant object recognition
We present a novel method for incorporating prior knowledge about invariances in object recognition for discriminant analysis. In contrast to conventional isotropic regularization...
Yung-Kyun Noh, Jihun Ham, Daniel D. Lee
97
Voted
ICASSP
2009
IEEE
15 years 4 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...
95
Voted
NIPS
2003
15 years 1 months ago
Kernels for Structured Natural Language Data
This paper devises a novel kernel function for structured natural language data. In the field of Natural Language Processing, feature extraction consists of the following two ste...
Jun Suzuki, Yutaka Sasaki, Eisaku Maeda
85
Voted
ICPR
2008
IEEE
16 years 1 months ago
Impulse noise removal by spectral clustering and regularization on graphs
In this paper we present a method for impulse noise removal that makes use of spectral clustering and graph regularization. The image is modeled as a graph and local spectral anal...
Olivier Lezoray, Vinh-Thong Ta, Abderrahim Elmoata...
111
Voted
CPC
2007
101views more  CPC 2007»
15 years 14 days ago
Colouring Random 4-Regular Graphs
We show that a random 4-regular graph asymptotically almost surely (a.a.s.) has chromatic number 3. The proof uses an efficient algorithm which a.a.s. 3colours a random 4-regular ...
Lingsheng Shi, Nicholas C. Wormald