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ECCC
2007
180views more  ECCC 2007»
14 years 10 months ago
Adaptive Algorithms for Online Decision Problems
We study the notion of learning in an oblivious changing environment. Existing online learning algorithms which minimize regret are shown to converge to the average of all locally...
Elad Hazan, C. Seshadhri
QSIC
2007
IEEE
15 years 4 months ago
Learning Effective Oracle Comparator Combinations for Web Applications
Web application testers need automated, effective approaches to validate the test results of complex, evolving web applications. In previous work, we developed a suite of automate...
Sara Sprenkle, Emily Hill, Lori L. Pollock
HEURISTICS
2008
92views more  HEURISTICS 2008»
14 years 10 months ago
Learning heuristics for basic block instruction scheduling
Instruction scheduling is an important step for improving the performance of object code produced by a compiler. A fundamental problem that arises in instruction scheduling is to ...
Abid M. Malik, Tyrel Russell, Michael Chase, Peter...
ISSRE
2007
IEEE
14 years 11 months ago
Using Machine Learning to Support Debugging with Tarantula
Using a specific machine learning technique, this paper proposes a way to identify suspicious statements during debugging. The technique is based on principles similar to Tarantul...
Lionel C. Briand, Yvan Labiche, Xuetao Liu
ICML
2000
IEEE
15 years 10 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall