6 citations · 19 across the 27 of their papers we have counts for
8 papers · 1 filter
Surrogate-Assisted Evolution for Efficient Multi-branch Connection Design in Deep Neural Networks
Fergal Stapleton, Daniel García Núñez, Yanan Sun +1
State-of-the-art Deep Neural Networks (DNNs) often incorporate multi-branch connections, enabling multi-scale feature extraction and enhancing the capture of diverse features. This…
Runtime Analysis of Evolutionary NAS for Multiclass Classification
Zeqiong Lv, Chao Qian, Yun Liu +2
Evolutionary neural architecture search (ENAS) is a key part of evolutionary machine learning, which commonly utilizes evolutionary algorithms (EAs) to automatically design high-pe…
A First Step Towards Runtime Analysis of Evolutionary Neural Architecture Search
Zeqiong Lv, Chao Qian, Yanan Sun
Evolutionary neural architecture search (ENAS) employs evolutionary algorithms to find high-performing neural architectures automatically, and has achieved great success. However,…
Differentiable Genetic Programming for High-dimensional Symbolic Regression
Peng Zeng, Xiaotian Song, Andrew Lensen +4
Symbolic regression (SR) is the process of discovering hidden relationships from data with mathematical expressions, which is considered an effective way to reach interpretable mac…
Architecture Augmentation for Performance Predictor Based on Graph Isomorphism
Xiangning Xie, Yuqiao Liu, Yanan Sun +2
Neural Architecture Search (NAS) can automatically design architectures for deep neural networks (DNNs) and has become one of the hottest research topics in the current machine lea…
Evolving Deep Neural Networks for Collaborative Filtering
Yuhan Fang, Yuqiao Liu, Yanan Sun
Collaborative Filtering (CF) is widely used in recommender systems to model user-item interactions. With the great success of Deep Neural Networks (DNNs) in various fields, advance…
BenchENAS: A Benchmarking Platform for Evolutionary Neural Architecture Search
Xiangning Xie, Yuqiao Liu, Yanan Sun +3
Neural architecture search (NAS), which automatically designs the architectures of deep neural networks, has achieved breakthrough success over many applications in the past few ye…
Evolving Deep Convolutional Neural Networks for Hyperspectral Image Denoising
Yuqiao Liu, Yanan Sun, Bing Xue +1
Hyperspectral images (HSIs) are susceptible to various noise factors leading to the loss of information, and the noise restricts the subsequent HSIs object detection and classifica…