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KDD
2004
ACM
150views Data Mining» more  KDD 2004»
14 years 8 months ago
A framework for ontology-driven subspace clustering
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
Jinze Liu, Wei Wang 0010, Jiong Yang
ICC
2007
IEEE
203views Communications» more  ICC 2007»
14 years 2 months ago
Distributed Data Aggregation Using Clustered Slepian-Wolf Coding in Wireless Sensor Networks
—Slepian-Wolf coding is a promising distributed source coding technique that can completely remove the data redundancy caused by the spatially correlated observations in wireless...
Pu Wang, Cheng Li, Jun Zheng
ECCV
2010
Springer
13 years 10 months ago
Learning Shape Segmentation Using Constrained Spectral Clustering and Probabilistic Label Transfer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
WACV
2005
IEEE
14 years 1 months ago
Multi-Layer Hierarchical Clustering of Pedestrian Trajectories for Automatic Counting of People in Video Sequences
In this paper we propose an approach to count the number of pedestrians, given a trajectory data set provided by a tracking system. The tracking process itself is treated as a bla...
David Biliotti, Gianluca Antonini, Jean-Philippe T...
COMGEO
2004
ACM
13 years 8 months ago
A local search approximation algorithm for k-means clustering
In k-means clustering we are given a set of n data points in d-dimensional space d and an integer k, and the problem is to determine a set of k points in d , called centers, to mi...
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu...