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» Learning from Our Mistakes with Defect Causal Analysis
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ICML
2005
IEEE
14 years 6 months ago
A causal approach to hierarchical decomposition of factored MDPs
We present Variable Influence Structure Analysis, an algorithm that dynamically performs hierarchical decomposition of factored Markov decision processes. Our algorithm determines...
Anders Jonsson, Andrew G. Barto
MSR
2006
ACM
13 years 11 months ago
Predicting defect densities in source code files with decision tree learners
With the advent of open source software repositories the data available for defect prediction in source files increased tremendously. Although traditional statistics turned out t...
Patrick Knab, Martin Pinzger, Abraham Bernstein
SIGIR
2002
ACM
13 years 4 months ago
A new family of online algorithms for category ranking
We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
Koby Crammer, Yoram Singer
FOCS
1995
IEEE
13 years 8 months ago
Tracking the Best Disjunction
Abstract. Littlestone developed a simple deterministic on-line learning algorithm for learning k-literal disjunctions. This algorithm (called Winnow) keeps one weight for each of t...
Peter Auer, Manfred K. Warmuth
KDD
2007
ACM
209views Data Mining» more  KDD 2007»
14 years 5 months ago
Temporal causal modeling with graphical granger methods
The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
Andrew Arnold, Yan Liu, Naoki Abe