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KDD
2008
ACM
119views Data Mining» more  KDD 2008»
16 years 7 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
16 years 7 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
KDD
2005
ACM
157views Data Mining» more  KDD 2005»
16 years 7 months ago
A fast kernel-based multilevel algorithm for graph clustering
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 7 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
VLSID
2002
IEEE
159views VLSI» more  VLSID 2002»
16 years 7 months ago
Challenges in the Design of a Scalable Data-Acquisition and Processing System-on-Silicon
Increasing complexity of the functionalities and the resultant growth in number of gates integrated in a chip coupled with shrinking geometries and short cycle time requirements br...
Karanth Shankaranarayana, Soujanna Sarkar, R. Venk...
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