

Deep Neural Evolution by Hitoshi Iba
Consequently, EC researchers are enthusiastic about applying their arsenal for the design and optimization of deep neural networks (DNN). This book brings together the recent progress in DL research where the focus is particularly on three sub-domains that integrate EC with DL: (1) EC for hyper-parameter optimization in DNN;-
Robot Evolution
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An Introduction to Metaheuristics for Optimization
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Lectures on Intelligent Systems
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Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms
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Coevolutionary Computation and Its Applications
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Visions of DNA Nanotechnology at 40 for the Next 40
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Cartesian Genetic Programming
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Bioinspired Computation in Combinatorial Optimization
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Self-organising Software
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Swarm Intelligence
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Evolution as Computation
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Algorithmic Bioprocesses
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General-Purpose Optimization Through Information Maximization
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Nature Inspired Optimisation for Delivery Problems
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Experimental Research in Evolutionary Computation
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Hyper-Heuristics: Theory and Applications
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Modelling in Molecular Biology
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Advances in Metaheuristics for Hard Optimization
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Foraging-Inspired Optimisation Algorithms
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Mobility in Process Calculi and Natural Computing
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Automating the Design of Data Mining Algorithms
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Contemporary Evolution Strategies
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Theory and Principled Methods for the Design of Metaheuristics
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Discrete and Topological Models in Molecular Biology
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Massively Parallel Evolutionary Computation on GPGPUs
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Multimodal Optimization by Means of Evolutionary Algorithms
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Computation in Living Cells
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Sensitivity Analysis for Neural Networks
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Reservoir Computing
| SKU | Unavailable |
| ISBN 13 | |
| ISBN 10 | |
| Title | Deep Neural Evolution |
| Author | Hitoshi Iba |
| Series | |
| Condition | Unavailable |
| Binding Type | |
| Publisher | |
| Year published | |
| Number of pages | |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |
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