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KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 6 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
PR
2006
152views more  PR 2006»
15 years 5 months ago
Edit distance-based kernel functions for structural pattern classification
A common approach in structural pattern classification is to define a dissimilarity measure on patterns and apply a distance-based nearest-neighbor classifier. In this paper, we i...
Michel Neuhaus, Horst Bunke
SOSP
2005
ACM
16 years 2 months ago
Mondrix: memory isolation for linux using mondriaan memory protection
This paper presents the design and an evaluation of Mondrix, a version of the Linux kernel with Mondriaan Memory Protection (MMP). MMP is a combination of hardware and software th...
Emmett Witchel, Junghwan Rhee, Krste Asanovic
CVPR
2011
IEEE
15 years 1 months ago
Graph Embedding Discriminant Analysis on Grassmannian Manifolds for Improved Image Set Matching
A convenient way of dealing with image sets is to represent them as points on Grassmannian manifolds. While several recent studies explored the applicability of discriminant analy...
Mehrtash Harandi, Sareh, Shirazi (National ICT Aus...
ICPR
2010
IEEE
15 years 8 months ago
Kernel-Based Implicit Regularization of Structured Objects
Weighted graph regularization provides a rich framework that allows to regularize functions defined over the vertices of a weighted graph. Until now, such a framework has been only...
François-Xavier Dupé, Sébastien Bougleux, Luc B...