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HIS
2007
14 years 12 months ago
Pareto-based Multi-Objective Machine Learning
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
Yaochu Jin
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
15 years 3 months ago
TestFul: using a hybrid evolutionary algorithm for testing stateful systems
This paper introduces TestFul, a framework for testing stateful systems and focuses on object-oriented software. TestFul employs a hybrid multi-objective evolutionary algorithm, t...
Matteo Miraz, Pier Luca Lanzi, Luciano Baresi
EMO
2005
Springer
123views Optimization» more  EMO 2005»
15 years 4 months ago
Initial Population Construction for Convergence Improvement of MOEAs
Nearly all Multi-Objective Evolutionary Algorithms (MOEA) rely on random generation of initial population. In large and complex search spaces, this random method often leads to an ...
Christian Haubelt, Jürgen Gamenik, Jürge...
ICDCS
2008
IEEE
15 years 4 months ago
Correlation-Aware Object Placement for Multi-Object Operations
A multi-object operation incurs communication or synchronization overhead when the requested objects are distributed over different nodes. The object pair correlations (the probab...
Ming Zhong, Kai Shen, Joel I. Seiferas
EVOW
2007
Springer
15 years 4 months ago
A Probabilistic Beam Search Approach to the Shortest Common Supersequence Problem
The Shortest Common Supersequence Problem (SCSP) is a well-known hard combinatorial optimization problem that formalizes many real world problems. This paper presents a novel rando...
Christian Blum, Carlos Cotta, Antonio J. Fern&aacu...