"Computational modeling"

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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Reference Vector-Assisted Adaptive Model Management for Surrogate-Assisted Many-Objective Optimization
Acquisition functions for surrogate-assisted many-objective optimization require a delicate balance between convergence and diversity. …
Qiqi Liu, Ran Cheng, Yaochu Jin, Martin Heiderich, Tobias Rodemann
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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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Surrogate-Assisted Expensive Many-Objective Optimization by Model Fusion
Surrogate-assisted evolutionary algorithms have played an important role in expensive optimization where a small number of …
Cheng He, Ran Cheng, Yaochu Jin, Xin Yao
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Surrogate-Assisted Cooperative Swarm Optimization of High-Dimensional Expensive Problems
Surrogate models have shown to be effective in assisting metaheuristic algorithms for solving computationally expensive complex …
Chaoli Sun, Yaochu Jin, Ran Cheng, Jinliang Ding, Jianchao Zeng
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