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Article
Open AccessSynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms
The development of algorithms to infer the structure of gene regulatory networks based on expression data is an important subject in bioinformatics research. Validation of these algorithms requires benchmark d...
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Chapter and Conference Paper
Testing microarray analysis methods with semi-synthetic data
The paper presents a technique for testing and comparison of microarray analysis methods. It is based on synthetic adjusting real microarray datasets with data that follow specific biological intuition (spike-...
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Chapter and Conference Paper
Combined Optimization of Feature Selection and Algorithm Parameters in Machine Learning of Language
Comparative machine learning experiments have become an important methodology in empirical approaches to natural language processing (i) to investigate which machine learning algorithms have the ‘right bias’ t...
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Chapter and Conference Paper
Solving CSP Instances Beyond the Phase Transition Using Stochastic Search Algorithms
When solving constraint satisfaction problems (CSPs) with stochastic search algorithms (SSAs) using the standard penalty function, it is not possible to show that there is no solution for a problem instance. I...
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Chapter and Conference Paper
SGA search dynamics on second order functions
By comparing its search dynamics to that of a simple O(n 2) heuristic, we are able to analyze the behavior of the simple genetic algorithm on second order functions, whose optimization is shown to be an NP-equiva...
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Chapter and Conference Paper
The effect of spin-flip symmetry on the performance of the simple GA
We use the one-dimensional nearest neighbor interaction functions (NNIs) to show how the presence of symmetry in a fitness function greatly influences the convergence behavior of the simple genetic algorithm (...
