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ICDM
2003
IEEE
220views Data Mining» more  ICDM 2003»
14 years 1 months ago
Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
AAAI
2008
13 years 11 months ago
A Variance Analysis for POMDP Policy Evaluation
Partially Observable Markov Decision Processes have been studied widely as a model for decision making under uncertainty, and a number of methods have been developed to find the s...
Mahdi Milani Fard, Joelle Pineau, Peng Sun
DAC
2005
ACM
13 years 10 months ago
Mapping statistical process variations toward circuit performance variability: an analytical modeling approach
A physical yet compact gate delay model is developed integrating short-channel effects and the Alpha-power law based timing model. This analytical approach accurately predicts bot...
Yu Cao, Lawrence T. Clark
BMCBI
2006
122views more  BMCBI 2006»
13 years 8 months ago
A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets
Background: Gene selection is an important step when building predictors of disease state based on gene expression data. Gene selection generally improves performance and identifi...
Carmen Lai, Marcel J. T. Reinders, Laura J. van't ...
RAID
2010
Springer
13 years 7 months ago
On Challenges in Evaluating Malware Clustering
Malware clustering and classification are important tools that enable analysts to prioritize their malware analysis efforts. The recent emergence of fully automated methods for ma...
Peng Li, Limin Liu, Debin Gao, Michael K. Reiter