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» An Empirical Study of Optimal Noise and Runtime Distribution...
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SAT
2010
Springer
165views Hardware» more  SAT 2010»
13 years 2 months ago
An Empirical Study of Optimal Noise and Runtime Distributions in Local Search
This paper presents a detailed empirical study of local search for Boolean satisfiability (SAT), highlighting several interesting properties, some of which were previously unknown...
Lukas Kroc, Ashish Sabharwal, Bart Selman
AI
1999
Springer
13 years 4 months ago
Towards a Characterisation of the Behaviour of Stochastic Local Search Algorithms for SAT
Stochastic local search (SLS) algorithms have been successfully applied to hard combinatorial problems from different domains. Due to their inherent randomness, the run-time behav...
Holger H. Hoos, Thomas Stützle
GECCO
2005
Springer
146views Optimization» more  GECCO 2005»
13 years 10 months ago
An empirical study of the robustness of two module clustering fitness functions
Two of the attractions of search-based software engineering (SBSE) derive from the nature of the fitness functions used to guide the search. These have proved to be highly robust...
Mark Harman, Stephen Swift, Kiarash Mahdavi
CP
2006
Springer
13 years 8 months ago
Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
IPPS
2007
IEEE
13 years 10 months ago
Optimizing Sorting with Machine Learning Algorithms
The growing complexity of modern processors has made the development of highly efficient code increasingly difficult. Manually developing highly efficient code is usually expen...
Xiaoming Li, María Jesús Garzar&aacu...