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ICML
2004
IEEE
16 years 7 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
HPDC
2002
IEEE
15 years 11 months ago
Multigrain Parallelism for Eigenvalue Computations on Networks of Clusters
Clusters of workstations have become a cost-effective means of performing scientific computations. However, large network latencies, resource sharing, and heterogeneity found in ...
James R. McCombs, Andreas Stathopoulos
AAAI
2008
15 years 9 months ago
Clustering via Random Walk Hitting Time on Directed Graphs
In this paper, we present a general data clustering algorithm which is based on the asymmetric pairwise measure of Markov random walk hitting time on directed graphs. Unlike tradi...
Mo Chen, Jianzhuang Liu, Xiaoou Tang
SDM
2008
SIAM
161views Data Mining» more  SDM 2008»
15 years 8 months ago
Efficient Maximum Margin Clustering via Cutting Plane Algorithm
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
Bin Zhao, Fei Wang, Changshui Zhang
INTR
2010
157views more  INTR 2010»
15 years 5 months ago
Classifying the user intent of web queries using k-means clustering
Purpose – Web search engines are frequently used by people to locate information on the Internet. However, not all queries have an informational goal. Instead of information, so...
Ashish Kathuria, Bernard J. Jansen, Carolyn Hafern...