Ran Cheng (程然)
Ran Cheng (程然)
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VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix
Existing vision-language pre-training (VLP) methods primarily rely on paired image-text datasets, which are either annotated by …
Teng Wang
,
Wenhao Jiang
,
Zhichao Lu
,
Feng Zheng
,
Ran Cheng
,
Chengguo Yin
,
Ping Luo
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URL
Large-scale Multiobjective Optimization via Problem Decomposition and Reformulation
Large-scale multiobjective optimization problems (LSMOPs) are challenging for existing approaches due to the complexity of objective …
Lianghao Li
,
Cheng He
,
Ran Cheng
,
Linqiang Pan
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DOI
Dimension Dropout for Evolutionary High-Dimensional Expensive Multiobjective Optimization
In the past decades, a number of surrogate-assisted evolutionary algorithms (SAEAs) have been developed to solve expensive …
Jianqing Lin
,
Cheng He
,
Ran Cheng
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DOI
Manifold Learning Inspired Mating Restriction for Evolutionary Constrained Multiobjective Optimization
Mating restriction strategies are capable of restricting the distribution of parent solutions for effective offspring generation in …
Lianghao Li
,
Cheng He
,
Ran Cheng
,
Linqiang Pan
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DOI
Multi-objective Neural Architecture Search with Almost No Training
In the recent past, neural architecture search (NAS) has attracted increasing attention from both academia and industries. Despite the …
Shengran Hu
,
Ran Cheng
,
Cheng He
,
Zhichao Lu
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DOI
Operator-Adapted Evolutionary Large-Scale Multiobjective Optimization for Voltage Transformer Ratio Error Estimation
Large-scale multiobjective optimization problems (LSMOPs) exist widely in real-world applications, and they are challenging for …
Changwu Huang
,
Lianghao Li
,
Cheng He
,
Ran Cheng
,
Xin Yao
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DOI
Population Sizing of Evolutionary Large-Scale Multiobjective Optimization
Large-scale multiobjective optimization problems (LSMOPs) are emerging and widely existed in real-world applications, which involve a …
Cheng He
,
Ran Cheng
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DOI
Efficient Evolutionary Deep Neural Architecture Search (NAS) by Noisy Network Morphism Mutation
Deep learning has achieved enormous breakthroughs in the field of image recognition. However, due to the time-consuming and error-prone …
Yiming Chen
,
Tianci Pan
,
Cheng He
,
Ran Cheng
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DOI
Iterated Problem Reformulation for Evolutionary Large-Scale Multiobjective Optimization
Due to the curse of dimensionality, two main issues remain challenging for applying evolutionary algorithms (EAs) to large-scale …
Cheng He
,
Ran Cheng
,
Ye Tian
,
Xingyi Zhang
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DOI
Techniques for Accelerating Multi-Objective Evolutionary Algorithms in PlatEMO
It has been widely recognized that evolutionary computation is one of the most effective techniques for solving complex optimization …
Ye Tian
,
Ran Cheng
,
Xingyi Zhang
,
Yaochu Jin
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DOI
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