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SDM
2007
SIAM
117views Data Mining» more  SDM 2007»
14 years 11 months ago
Discriminating Subsequence Discovery for Sequence Clustering
In this paper, we explore the discriminating subsequencebased clustering problem. First, several effective optimization techniques are proposed to accelerate the sequence mining p...
Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Ka...
ICSP
1993
84views more  ICSP 1993»
14 years 11 months ago
A Role-Based Empirical Process Modeling Environment
Much contemporary development process research is based on analyses of process steps, their duration, and the events they propagate. Our initial research in large, mature telecomm...
Brendan G. Cain, James Coplien
JMLR
2011
167views more  JMLR 2011»
14 years 4 months ago
Logistic Stick-Breaking Process
A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are ...
Lu Ren, Lan Du, Lawrence Carin, David B. Dunson
SAC
2005
ACM
15 years 3 months ago
On unit task linear-nonlinear two-cluster scheduling problem
In parallel and distributed processing, tasks are ordinarily clustered and assigned to different processors or machines before they are scheduled. The assignment of tasks to proc...
Zhichun Xiao, Wing Ning Li, John Jing-Fu Jenq
NIPS
2001
14 years 11 months ago
An Efficient Clustering Algorithm Using Stochastic Association Model and Its Implementation Using Nanostructures
This paper describes a clustering algorithm for vector quantizers using a "stochastic association model". It offers a new simple and powerful softmax adaptation rule. Th...
Takashi Morie, Tomohiro Matsuura, Makoto Nagata, A...