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» Learning Spectral Clustering
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ICML
2006
IEEE
14 years 9 months ago
Discriminative cluster analysis
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Fernando De la Torre, Takeo Kanade
WWW
2010
ACM
13 years 8 months ago
Cross-domain sentiment classification via spectral feature alignment
Sentiment classification aims to automatically predict sentiment polarity (e.g., positive or negative) of users publishing sentiment data (e.g., reviews, blogs). Although traditio...
Sinno Jialin Pan, Xiaochuan Ni, Jian-Tao Sun, Qian...

Source Code
2231views
15 years 2 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
LKR
2008
13 years 10 months ago
Identification of MCMC Samples for Clustering
Abstract. For clustering problems, many studies use just MAP assignments to show clustering results instead of using whole samples from a MCMC sampler. This is because it is not st...
Kenichi Kurihara, Tsuyoshi Murata, Taisuke Sato
ICML
2005
IEEE
14 years 9 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...