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» Stability of k -Means Clustering
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KDD
2007
ACM
178views Data Mining» more  KDD 2007»
15 years 10 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»
14 years 11 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»
14 years 9 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
15 years 3 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»
15 years 2 months 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