Abstract Network Intrusion Detection (NID) becomes significantly important for protecting the
security of information systems, as the frequency and complexity of network attacks are …

Transferable neural architecture search (TNAS) has been introduced to design efficient
neural architectures for multiple tasks, to enhance the practical applicability of NAS in real …

In cases of frequent problem-solving of multiobjective optimization tasks from a domain due
to changing conditions or problem features, a growing number of individual tasks will be …

The recent proliferation of edge computing has led to the deployment of deep neural
networks (DNNs) on edge devices like smartphones and IoT devices to serve end users …

The robustness of neural networks in image classification is important to resist adversarial
attacks. Although many researchers proposed to enhance the network robustness by …

Neural architecture search (NAS) based on differentiable methods has made significant
progress in both search cost (GPU-days and GPU memory consumption) and network …

A number of Neural Architecture Search (NAS) methods have been proposed to automate
the design of Convolutional Neural Networks (CNNs). However, they typically require …

Recently, a novel paradigm has been proposed for reinforcement learning-based NAS
agents, that revolves around the incremental improvement of a given architecture. We …

In recent years, many researchers have adopted neural architecture search (NAS)
techniques to automatically design generative adversarial networks (GANs). However, due …

Evolutionary computation (EC) is a kind of population-based search method, drawing
inspiration from natural selection and gene inheritance. Although EC has shown advantages …