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KDD
2004
ACM
113views Data Mining» more  KDD 2004»
16 years 7 months ago
Learning spatially variant dissimilarity (SVaD) measures
Clustering algorithms typically operate on a feature vector representation of the data and find clusters that are compact with respect to an assumed (dis)similarity measure betwee...
Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agra...
CVPR
2007
IEEE
16 years 8 months ago
Adaptive Distance Metric Learning for Clustering
A good distance metric is crucial for unsupervised learning from high-dimensional data. To learn a metric without any constraint or class label information, most unsupervised metr...
Jieping Ye, Zheng Zhao, Huan Liu
CVPR
2007
IEEE
16 years 8 months ago
Fiber Tract Clustering on Manifolds With Dual Rooted-Graphs
We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to gene...
Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero, Al...
155
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ICML
2007
IEEE
16 years 7 months ago
Relational clustering by symmetric convex coding
Relational data appear frequently in many machine learning applications. Relational data consist of the pairwise relations (similarities or dissimilarities) between each pair of i...
Bo Long, Zhongfei (Mark) Zhang, Xiaoyun Wu, Philip...
ICDM
2008
IEEE
230views Data Mining» more  ICDM 2008»
16 years 1 months ago
Clustering Distributed Time Series in Sensor Networks
Event detection is a critical task in sensor networks, especially for environmental monitoring applications. Traditional solutions to event detection are based on analyzing one-sh...
Jie Yin, Mohamed Medhat Gaber