Co-evolving parasites improve simulated evolution as an optimization procedure
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Kernel Nearest-Neighbor Algorithm
Neural Processing Letters
Dynamic Training Subset Selection for Supervised Learning in Genetic Programming
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Margin based feature selection - theory and algorithms
ICML '04 Proceedings of the twenty-first international conference on Machine learning
The Genetic Kernel Support Vector Machine: Description and Evaluation
Artificial Intelligence Review
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
Evolutionary tuning of multiple SVM parameters
Neurocomputing
Training genetic programming on half a million patterns: an example from anomaly detection
IEEE Transactions on Evolutionary Computation
Evolving kernels for support vector machine classification
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Multi-optimization improves genetic programming generalization ability
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Creation of Specific-to-Problem Kernel Functions for Function Approximation
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
A survey on the application of genetic programming to classification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Optimising multiple kernels for SVM by genetic programming
EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
Evolutionary computation for supervised learning
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed optimization problem; ii) non-linear learning can be brought into linear learning thanks to the kernel trick and the mapping of the initial search space onto a high dimensional feature space. The kernel is designed by the ML expert and it governs the efficiency of the SVM approach. In this paper, a new approach for the automatic design of kernels by Genetic Programming, called the Evolutionary Kernel Machine (EKM), is presented. EKM combines a well-founded fitness function inspired from the margin criterion, and a co-evolution framework ensuring the computational scalability of the approach. Empirical validation on standard ML benchmark demonstrates that EKM is competitive using state-of-the-art SVMs with tuned hyper-parameters.