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COLT
2004
Springer
14 years 2 months ago
On the Convergence of Spectral Clustering on Random Samples: The Normalized Case
Given a set of n randomly drawn sample points, spectral clustering in its simplest form uses the second eigenvector of the graph Laplacian matrix, constructed on the similarity gra...
Ulrike von Luxburg, Olivier Bousquet, Mikhail Belk...
FPL
2004
Springer
72views Hardware» more  FPL 2004»
14 years 2 months ago
Simultaneous Timing Driven Clustering and Placement for FPGAs
Traditional placement algorithms for FPGAs are normally carried out on a fixed clustering solution of a circuit. The impact of clustering on wirelength and delay of the placement s...
Gang Chen, Jason Cong
PAKDD
2004
ACM
183views Data Mining» more  PAKDD 2004»
14 years 2 months ago
Constraint-Based Graph Clustering through Node Sequencing and Partitioning
This paper proposes a two-step graph partitioning method to discover constrained clusters with an objective function that follows the well-known minmax clustering principle. Compar...
Yu Qian, Kang Zhang, Wei Lai
SDM
2004
SIAM
212views Data Mining» more  SDM 2004»
13 years 10 months ago
Clustering with Bregman Divergences
A wide variety of distortion functions, such as squared Euclidean distance, Mahalanobis distance, Itakura-Saito distance and relative entropy, have been used for clustering. In th...
Arindam Banerjee, Srujana Merugu, Inderjit S. Dhil...
NIPS
2004
13 years 10 months ago
Detecting Significant Multidimensional Spatial Clusters
Assume a uniform, multidimensional grid of bivariate data, where each cell of the grid has a count ci and a baseline bi. Our goal is to find spatial regions (d-dimensional rectang...
Daniel B. Neill, Andrew W. Moore, Francisco Pereir...