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» Two Algorithms for Inducing Causal Models from Data
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ISSTA
2010
ACM
14 years 2 days ago
Analyzing concurrency bugs using dual slicing
Recently, there has been much interest in developing analyzes to detect concurrency bugs that arise because of data races, atomicity violations, execution omission, etc. However, ...
Dasarath Weeratunge, Xiangyu Zhang, William N. Sum...
FAST
2009
13 years 6 months ago
Causality-Based Versioning
Versioning file systems provide the ability to recover from a variety of failures, including file corruption, virus and worm infestations, and user mistakes. However, using versio...
Kiran-Kumar Muniswamy-Reddy, David A. Holland
ARTMED
1999
92views more  ARTMED 1999»
13 years 8 months ago
Two-Stage Machine Learning model for guideline development
We present a Two-Stage Machine Learning (ML) model as a data mining method to develop practice guidelines and apply it to the problem of dementia staging. Dementia staging in clin...
Subramani Mani, William Rodman Shankle, Malcolm B....
UAI
1993
13 years 9 months ago
Using Causal Information and Local Measures to Learn Bayesian Networks
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...
Wai Lam, Fahiem Bacchus
KDD
2008
ACM
174views Data Mining» more  KDD 2008»
14 years 8 months ago
Automatic identification of quasi-experimental designs for discovering causal knowledge
Researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large databases. Quasi-experimental designs (QEDs) exploi...
David D. Jensen, Andrew S. Fast, Brian J. Taylor, ...