Part I Preliminaries
Chapter 1 Evolutionary Computation and meta-heuristics
Chapter 2 A Shallow Introduction to Deep Neural Networks
Part II Hyper-parameter Optimization
Chapter 3 On the Assessment of Nature-Inspired Meta-Heuristic Optimization Techniques to Fine-Tune Deep Belief Networks
Chapter 4 Automated development of DNN based spoken language systems using evolutionary algorithms
Chapter 5 Search heuristics for the optimization of DBN for Time Series Forecasting
Part III Structure Optimization
Chapter 6 Particle Swarm Optimisation for Evolving Deep Convolutional Neural Networks for Image Classification: Single- and Multi-objective Approaches Chapter 7 Designing Convolutional Neural Network Architectures Using Cartesian Genetic Programming
Chapter 8 Fast Evolution of CNN Architecture for Image Classificaiton
Part IV Deep Neuroevolution
Chapter 9 Discovering Gated Recurrent Neural Network Architectures
Chapter 10 Investigating Deep Recurrent Connections and Recurrent Memory Cells Using Neuro-Evolution
Chapter 11 Neuroevolution of Generative Adversarial Networks
Part V Applications and Others
Chapter 12 Evolving deep neural networks for X-ray based detection of dangerous objects Chapter 13 Evolving the architecture and hyperparameters of DNNs for malware detection
Chapter 14 Data Dieting in GAN Training
Chapter 15 One-Pixel Attack: Understanding and Improving Deep Neural Networks with Evolutionary Computation
About the Author: Hitoshi Iba received his Ph.D. degree from The University of Tokyo, Japan, in 1990. From 1990 to 1998, he was with the Electro Technical Laboratory in Ibaraki, Japan. Since 1998, he has been with The University of Tokyo, where he is currently a professor in the Graduate School of Information Science and Technology. His research interests include evolutionary computation, artificial life, artificial intelligence, and robotics. He is an associate editor of the Journal of Genetic Programming and Evolvable Machines (GPEM). Dr. Iba is also is an underwater naturalist and experienced Professional Association of Diving Instructors (PADI) divemaster, having completed more than a thousand dives.
Nasimul Noman received his Ph.D. degree from The University of Tokyo, Japan, in 2007. He was a faculty member in the Department of Computer Science and Engineering, University of Dhaka, Bangladesh, from 2002 to 2012. In 2013, he joined the School of Electrical Engineering and Computing at The University of Newcastle, Australia, and currently he is working as a senior lecturer there. His research interests include evolutionary computation, computational biology, bioinformatics, and machine learning.
