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ICML
2007
IEEE
16 years 7 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney
ICML
2006
IEEE
16 years 7 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
ICML
2005
IEEE
16 years 7 months ago
Proto-value functions: developmental reinforcement learning
This paper presents a novel framework called proto-reinforcement learning (PRL), based on a mathematical model of a proto-value function: these are task-independent basis function...
Sridhar Mahadevan
165
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ICSE
2008
IEEE-ACM
16 years 7 months ago
Sufficient mutation operators for measuring test effectiveness
Mutants are automatically-generated, possibly faulty variants of programs. The mutation adequacy ratio of a test suite is the ratio of non-equivalent mutants it is able to identif...
Akbar Siami Namin, James H. Andrews, Duncan J. Mur...
SIGSOFT
2007
ACM
16 years 7 months ago
A specification-based approach to testing software product lines
This paper presents a specification-based approach for systematic testing of products from a software product line. Our approach uses specifications given as formulas in Alloy, a ...
Engin Uzuncaova, Daniel Garcia, Sarfraz Khurshid, ...
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