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» Clustering Fiber Traces Using Normalized Cuts
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JMLR
2006
124views more  JMLR 2006»
14 years 9 months ago
Fast SDP Relaxations of Graph Cut Clustering, Transduction, and Other Combinatorial Problem
The rise of convex programming has changed the face of many research fields in recent years, machine learning being one of the ones that benefitted the most. A very recent develop...
Tijl De Bie, Nello Cristianini
UAI
2003
14 years 10 months ago
Learning Generative Models of Similarity Matrices
Recently, spectral clustering (a.k.a. normalized graph cut) techniques have become popular for their potential ability at finding irregularlyshaped clusters in data. The input to...
Rómer Rosales, Brendan J. Frey
KDD
2005
ACM
157views Data Mining» more  KDD 2005»
15 years 9 months ago
A fast kernel-based multilevel algorithm for graph clustering
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
ICCV
2003
IEEE
15 years 11 months ago
Automatic Video Summarization by Graph Modeling
We propose a unified approach for summarization based on the analysis of video structures and video highlights. Our approach emphasizes both the content balance and perceptual qua...
Chong-Wah Ngo, Yu-Fei Ma, HongJiang Zhang

Source Code
2231views
16 years 3 months ago
The Berkeley Segmentation Engine (BSE)
The code is a (good, in my opinion) implementation of a segmentation engine based on normalised cuts (a spectral clustering algorithm) and a pixel affinity matrix calculation algor...
Charless Fowlkes