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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
AICS
2009
14 years 11 months ago
Analysis of the Effect of Unexpected Outliers in the Classification of Spectroscopy Data
Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume all classes are characte...
Frank G. Glavin, Michael G. Madden
ICCAD
2000
IEEE
97views Hardware» more  ICCAD 2000»
15 years 6 months ago
Error Catch and Analysis for Semiconductor Memories Using March Tests
We present an error catch and analysis (ECA) system for semiconductor memories. The system consists of a test algorithm generator called TAGS, a fault simulator called RAMSES, and...
Chi-Feng Wu, Chih-Tsun Huang, Chih-Wea Wang, Kuo-L...
PAMI
2010
276views more  PAMI 2010»
15 years 4 days ago
Local-Learning-Based Feature Selection for High-Dimensional Data Analysis
—This paper considers feature selection for data classification in the presence of a huge number of irrelevant features. We propose a new feature selection algorithm that addres...
Yijun Sun, Sinisa Todorovic, Steve Goodison
DAC
2004
ACM
16 years 2 months ago
Fast statistical timing analysis handling arbitrary delay correlations
CT An efficient statistical timing analysis algorithm that can handle arbitrary (spatial and structural) causes of delay correlation is described. The algorithm derives the entire ...
Michael Orshansky, Arnab Bandyopadhyay