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PAKDD
2011
ACM
214views Data Mining» more  PAKDD 2011»
14 years 5 months ago
Spectral Analysis of k-Balanced Signed Graphs
Abstract. Previous studies on social networks are often focused on networks with only positive relations between individual nodes. As a significant extension, we conduct the spectr...
Leting Wu, Xiaowei Ying, Xintao Wu, Aidong Lu, Zhi...
DATE
2003
IEEE
99views Hardware» more  DATE 2003»
15 years 7 months ago
RF-BIST: Loopback Spectral Signature Analysis
Built-In Self-Test (BIST) becomes important also for more complex structures like complete front-ends. In order to bring down the costs for the test overhead, Spectral Signature A...
Doris Lupea, Udo Pursche, Hans-Joachim Jentschel
CORR
2010
Springer
130views Education» more  CORR 2010»
15 years 27 days ago
Spectral methods for the detection of network community structure: a comparative analysis
Spectral analysis has been successfully applied to the detection of community structure of networks, respectively being based on the adjacency matrix, the standard Laplacian matrix...
Hua-Wei Shen, Xue-Qi Cheng
SDM
2007
SIAM
137views Data Mining» more  SDM 2007»
15 years 3 months ago
Semi-supervised Feature Selection via Spectral Analysis
Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
Zheng Zhao, Huan Liu
PAKDD
2009
ACM
209views Data Mining» more  PAKDD 2009»
15 years 11 months ago
Approximate Spectral Clustering.
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...