Deep Learning

Ternary Compression for Communication-Efficient Federated Learning
Learning over massive data stored in different locations is essential in many real-world applications. However, sharing data is full of …
Jinjin Xu, Wenli Du, Yaochu Jin, Wangli He, Ran Cheng
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Neural Architecture Search as Multiobjective Optimization Benchmarks: Problem Formulation and Performance Assessment
The ongoing advancements in network architecture design have led to remarkable achievements in deep learning across various challenging …
Zhichao Lu, Ran Cheng, Yaochu Jin, Kay Chen Tan, Kalyanmoy Deb
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An Inverse Design Method for Supercritical Airfoil Based on Conditional Generative Models
Inverse design has long been an efficient and powerful design tool in the aircraft industry. In this paper, a novel inverse design …
Jing Wang, Runze Li, Cheng He, Haixin Chen, Ran Cheng, Chen Zhai, Miao Zhang
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Evolutionary Multiobjective Optimization Driven by Generative Adversarial Networks (GANs)
Recently, increasing works have been proposed to drive evolutionary algorithms using machine-learning models. Usually, the performance …
Cheng He, Shihua Huang, Ran Cheng, Kay Chen Tan, Yaochu Jin
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Constructing an Automatic Diagnosis and Severity-classification Model for Acromegaly using Facial Photographs by Deep Learning
Due to acromegaly’s insidious onset and slow progression, its diagnosis is usually delayed, thus causing severe complications and …
Yanguo Kong, Xiangyi Kong, Cheng He, Changsong Liu, Liting Wang, Lijuan Su, Jun Gao, Qi Guo, Ran Cheng
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