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» Smoothed Analysis of Multiobjective Optimization
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FUIN
2011
358views Cryptology» more  FUIN 2011»
12 years 11 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...
EMO
2006
Springer
124views Optimization» more  EMO 2006»
13 years 11 months ago
I-MODE: An Interactive Multi-objective Optimization and Decision-Making Using Evolutionary Methods
With the popularity of efficient multi-objective evolutionary optimization (EMO) techniques and the need for such problem-solving activities in practice, EMO methodologies and EMO ...
Kalyanmoy Deb, Shamik Chaudhuri
IJCNN
2006
IEEE
14 years 1 months ago
Generalization Improvement in Multi-Objective Learning
— Several heuristic methods have been suggested for improving the generalization capability in neural network learning, most of which are concerned with a single-objective (SO) l...
Lars Gräning, Yaochu Jin, Bernhard Sendhoff
CEC
2008
IEEE
14 years 2 months ago
High-level synthesis with multi-objective genetic algorithm: A comparative encoding analysis
— The high-level synthesis process involves three interdependent and NP-complete optimization problems: (i) the operation scheduling, (ii) the resource allocation, and (iii) the ...
Christian Pilato, Daniele Loiacono, Fabrizio Ferra...
GECCO
2008
Springer
109views Optimization» more  GECCO 2008»
13 years 8 months ago
A tunable model for multi-objective, epistatic, rugged, and neutral fitness landscapes
The fitness landscape of a problem is the relation between the solution candidates and their reproduction probability. In order to understand optimization problems, it is essenti...
Thomas Weise, Stefan Niemczyk, Hendrik Skubch, Rol...