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BMCBI
2006
123views more  BMCBI 2006»
15 years 6 months ago
Characterizing disease states from topological properties of transcriptional regulatory networks
Background: High throughput gene expression experiments yield large amounts of data that can augment our understanding of disease processes, in addition to classifying samples. He...
David Tuck, Harriet Kluger, Yuval Kluger
ICSE
2007
IEEE-ACM
16 years 6 months ago
Using GUI Run-Time State as Feedback to Generate Test Cases
This paper presents a new automated model-driven technique to generate test cases by using feedback from the execution of a "seed test suite" on an application under tes...
Xun Yuan, Atif M. Memon
DAMON
2009
Springer
16 years 27 days ago
Cache-conscious buffering for database operators with state
Database processes must be cache-efficient to effectively utilize modern hardware. In this paper, we analyze the importance of temporal locality and the resultant cache behavior ...
John Cieslewicz, William Mee, Kenneth A. Ross
NN
2007
Springer
162views Neural Networks» more  NN 2007»
15 years 5 months ago
Learning grammatical structure with Echo State Networks
Echo State Networks (ESNs) have been shown to be effective for a number of tasks, including motor control, dynamic time series prediction, and memorizing musical sequences. Howeve...
Matthew H. Tong, Adam D. Bickett, Eric M. Christia...
ICASSP
2011
IEEE
14 years 10 months ago
Online Kernel SVM for real-time fMRI brain state prediction
The Support Vector Machine (SVM) methodology is an effective, supervised, machine learning method that gives stateof-the-art performance for brain state classification from funct...
Yongxin Taylor Xi, Hao Xu, Ray Lee, Peter J. Ramad...