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ICPR
2008
IEEE
14 years 9 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...
CORR
2007
Springer
129views Education» more  CORR 2007»
13 years 8 months ago
A Tutorial on Spectral Clustering
In recent years, spectral clustering has become one of the most popular modern clustering algorithms. It is simple to implement, can be solved efficiently by standard linear algeb...
Ulrike von Luxburg
LION
2009
Springer
125views Optimization» more  LION 2009»
14 years 3 months ago
New Bounds on the Clique Number of Graphs Based on Spectral Hypergraph Theory
This work introduces new bounds on the clique number of graphs derived from a result due to S´os and Straus, which generalizes the Motzkin-Straus Theorem to a specific class of h...
Samuel Rota Bulò, Marcello Pelillo
ICMCS
2007
IEEE
180views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Discrete Regularization for Perceptual Image Segmentation via Semi-Supervised Learning and Optimal Control
In this paper, we present a regularization approach on discrete graph spaces for perceptual image segmentation via semisupervised learning. In this approach, first, a spectral cl...
Hongwei Zheng, Olaf Hellwich
ACL
2006
13 years 10 months ago
Unsupervised Relation Disambiguation Using Spectral Clustering
This paper presents an unsupervised learning approach to disambiguate various relations between name entities by use of various lexical and syntactic features from the contexts. I...
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu ...