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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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Adaptive Offspring Generation for Evolutionary Large-Scale Multiobjective Optimization
Offspring generation plays an important role in evolutionary multiobjective optimization. However, generating promising candidate …
Cheng He, Ran Cheng, Danial Yazdani
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Hybrid attention-based transformer block model for distant supervision relation extraction
With an exponential explosive growth of various digital text information, it is challenging to efficiently obtain specific knowledge …
Yan Xiao, Yaochu Jin, Ran Cheng, Kuangrong Hao
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Revisiting Self-Training for Few-Shot Learning of Language Model
As unlabeled data carry rich task-relevant information, they are proven useful for few-shot learning of language model. The question is …
Yiming Chen, Yan Zhang, Chen Zhang, Grandee Lee, Ran Cheng, Haizhou Li
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A Survey of Evolutionary Continuous Dynamic Optimization Over Two Decades—Part A
Many real-world optimization problems are dynamic. The field of dynamic optimization deals with such problems where the search space …
Danial Yazdani, Ran Cheng, Donya Yazdani, Jürgen Branke, Yaochu Jin, Xin Yao
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End-to-End Dense Video Captioning with Parallel Decoding
Dense video captioning aims to generate multiple associated captions with their temporal locations from the video. Previous methods …
Teng Wang, Ruimao Zhang, Zhichao Lu, Feng Zheng, Ran Cheng, Ping Luo
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FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
Recent advancements in deep neural networks have made remarkable leap-forwards in dense image prediction. However, the issue of feature …
Shihua Huang, Zhichao Lu, Ran Cheng, Cheng He
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Efficient Evolutionary Neural Architecture Search by Modular Inheritable Crossover
Deep neural networks are widely used in the domain of image classification, and a large number of excellent deep neural networks have …
Cheng He, Hao Tan, Shihua Huang, Ran Cheng
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Evolutionary Large-Scale Multi-Objective Optimization: A Survey
Multi-objective evolutionary algorithms (MOEAs) have shown promising performance in solving various optimization problems, but their …
Ye Tian, Langchun Si, Xingyi Zhang, Ran Cheng, Cheng He, Kay Tan, Yaochu Jin
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Adaptive Dropout for High-dimensional Expensive Multiobjective Optimization
Various works have been proposed to solve expensive multiobjective optimization problems (EMOPs) using surrogate-assisted evolutionary …
Jianqing Lin, Cheng He, Ran Cheng
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