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DEAP: evolutionary algorithms made easy
TLDR
A novel evolutionary computation framework that combines the flexibility and power of the Python programming language with a clean and lean core of transparent EC components that both facilitate rapid prototyping and testing of new EA ideas and encourage creativeness through simplicity and explicit algorithms. Expand
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Genericity in Evolutionary Computation Software Tools: Principles and Case-study
TLDR
This paper deals with the need for generic software development tools in evolutionary computations. Expand
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Robustness to Adversarial Examples through an Ensemble of Specialists
TLDR
We are proposing to use an ensemble of diverse specialists, where speciality is defined according to the confusion matrix, to make CNNs more robust to adversarial examples. Expand
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Genetic Programming, Validation Sets, and Parsimony Pressure
TLDR
This paper is an investigation on two methods to improve generalization in GP-based learning: 1) the selection of the best-of-run individuals using a three data sets methodology and 2) the application of parsimony pressure in order to reduce the complexity of the solutions. Expand
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Ensemble learning for free with evolutionary algorithms?
TLDR
The Evolutionary Ensemble Learning (EEL) approach presented in this paper features two contributions. Expand
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DEAP: a python framework for evolutionary algorithms
TLDR
DEAP (Distributed Evolutionary Algorithms in Python) is a novel volutionary computation framework for rapid prototyping and testing of ideas. Expand
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Probabilistic Sensing Model for Sensor Placement Optimization Based on Line-of-Sight Coverage
TLDR
This paper proposes a probabilistic sensor model for the optimization of sensor placement. Expand
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Character recognition experiments using Unipen data
TLDR
This paper presents experiments that compare the performances of several versions of a regional-fuzzy representation (RFR) developed for cursive handwriting recognition (CHR). Expand
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Open BEAGLE: A New Versatile C++ Framework for Evolutionary Computation
TLDR
This paper introduces a new Evolutionary Computation framework named Open BEAGLE, that we have been developing and improving since 1999. Expand
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A GIS Based Wireless Sensor Network Coverage Estimation and Optimization: A Voronoi Approach
TLDR
This paper presents a survey of the existing solutions for geosensor network optimization that use Voronoi diagram and Delaunay triangulation and identifies their limitations in a real world application. Expand
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