Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-valued Optimization Problem

Autor: Pitzer, Erik, Kronberger, Gabriel

Publikováno v: Pitzer E. et al., Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-Valued Optimization Problem. In: Moreno-D\'iaz R. et al. (eds) Computer Aided Systems Theory. Lecture Notes in Computer Science, Vol. 9520, 2015

The typical methods for symbolic regression produce rather abrupt changes in solution candidates. In this work, we have tried to transform symbolic regression from an optimization problem, with a landscape that is so rugged that typical analysis meth

Externí odkaz: http://arxiv.org/abs/2108.03274

DSGeo: Software tools for cross-platform analysis of gene expression data in GEO

Autor: Lacson, Ronilda, Pitzer, Erik, Kim, Jihoon, Galante, Pedro, Hinske, Christian, Ohno-Machado, Lucila

Publikováno v: In Journal of Biomedical Informatics 2010 43(5):709-715

Towards large-scale sample annotation in gene expression repositories.

Autor: Pitzer, Erik^1,2 erik.pitzer@fh-hagenberg.at, Lacson, Ronilda¹ rlacson@dsg.harvard.edu, Hinske, Christian¹ chinske@alum.mit.edu, Kim, Jihoon¹ jhkim@dsg.harvard.edu, Galante, Pedro A. F.^1,3 pgalante@ludwig.org.br, Ohno-Machado, Lucila¹ machado@dsg.harvard.edu

Publikováno v: BMC Bioinformatics. 2009 Supplement 9, Vol. 10, Special section p1-6. 6p. 1 Diagram, 1 Chart, 1 Graph.

Metaheuristic Algorithms for the Quadratic Assignment Problem: Performance and Comparison.

Autor: Beham, Andreas, Affenzeller, Michael, Pitzer, Erik

Publikováno v: Innovative Technologies in Management & Science; 2015, p171-190, 20p

Smooth Symbolic Regression: Transformation of Symbolic Regression into a Real-Valued Optimization Problem.

Autor: Pitzer, Erik, Kronberger, Gabriel

Publikováno v: Computer Aided Systems Theory - EUROCAST 2015; 2015, p375-383, 9p