Automatic Feature Generation for Handwritten Digit Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian classification (AutoClass): theory and results
Advances in knowledge discovery and data mining
Analysis of Class Separation and Combination of Class-Dependent Features for Handwriting Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Selection for Support Vector Machines by Means of Genetic Algorithms
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
Fast SVM Training Algorithm with Decomposition on Very Large Data Sets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evolutionary strategies for multi-scale radial basis function kernels in support vector machines
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies
Proceedings of the 8th annual conference on Genetic and evolutionary computation
An analysis of mutative σ-self-adaptation on linear fitness functions
Evolutionary Computation
Controlling overfitting with multi-objective support vector machines
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Learning Handwritten Digit Recognition by the Max-Min Posterior Pseudo-Probabilities Method
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
Multi-objective model selection for support vector machines
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Evolving an expert checkers playing program without using humanexpertise
IEEE Transactions on Evolutionary Computation
Evolutionary Design of Neural Network Architectures Using a Descriptive Encoding Language
IEEE Transactions on Evolutionary Computation
Tuning of the structure and parameters of a neural network using an improved genetic algorithm
IEEE Transactions on Neural Networks
Learning polynomial feedforward neural networks by genetic programming and backpropagation
IEEE Transactions on Neural Networks
Mutation-based genetic neural network
IEEE Transactions on Neural Networks
Hybrid Multiobjective Evolutionary Design for Artificial Neural Networks
IEEE Transactions on Neural Networks
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The optimization method is one of key issues in discriminative learning of pattern classifiers. This paper proposes a hybrid approach of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and the gradient decent method for optimizing Bayesian classifiers under the SOFT target based Max-Min posterior Pseudo-probabilities (Soft-MMP) learning framework. In our hybrid optimization approach, the weighted mean of the parent population in the CMA-ES is adjusted by exploiting the gradient information of objective function, based on which the offspring is generated. As a result, the efficiency and the effectiveness of the CMA-ES are improved. We apply the Soft-MMP with the proposed hybrid optimization approach to handwritten digit recognition. The experiments on the CENPARMI database show that our handwritten digit classifier outperforms other state-of-the-art techniques. Furthermore, our hybrid optimization approach behaved better than not only the single gradient decent method but also the single CMA-ES in the experiments.