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» Stability of k -Means Clustering
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KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 8 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
SDM
2003
SIAM
110views Data Mining» more  SDM 2003»
13 years 9 months ago
Mixture Models and Frequent Sets: Combining Global and Local Methods for 0-1 Data
We study the interaction between global and local techniques in data mining. Specifically, we study the collections of frequent sets in clusters produced by a probabilistic clust...
Jaakko Hollmén, Jouni K. Seppänen, Hei...
COMBINATORICS
2007
55views more  COMBINATORICS 2007»
13 years 8 months ago
Clusters in a Multigraph with Elevated Density
In this paper, we prove that in a multigraph whose density Γ exceeds the maximum vertex degree ∆, the collection of minimal clusters (maximally dense sets of vertices) is cycle...
Mark K. Goldberg
SSS
2005
Springer
14 years 1 months ago
Synchronous vs. Asynchronous Unison
This paper considers the self-stabilizing unison problem. The contribution of this paper is threefold. First, we establish that when any self-stabilizing asynchronous unison protoc...
Christian Boulinier, Franck Petit, Vincent Villain
ISPD
1998
ACM
110views Hardware» more  ISPD 1998»
14 years 9 days ago
Performance-driven soft-macro clustering and placement by preserving HDL design hierarchy
In this paper, we present a performance-driven softmacro clustering and placement method which preserves HDL design hierarchy to guide the soft-macro placement process. We also pr...
Hsiao-Pin Su, Allen C.-H. Wu, Youn-Long Lin