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22 results found in all.

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16	Federated mutual learning: a collaborative machine learning method for heterogeneous data, models, and objectives Author(s):Tao SHEN, Jie ZHANG, Xinkang JIA, Fengda ZHANG, Zheqi LV, Kun KUANG, Chao WU, Fei WU Clicked:2203 Download:2370 Cited:0 <Full Text> <PPT> 666 Frontiers of Information Technology & Electronic Engineering 2023 Vol.24 No.10 P.1390-1402 DOI:10.1631/FITEE.2300098
17	Communication efficiency optimization of federated learning for computing and network convergence of 6G networks Author(s):Yizhuo CAI, Bo LEI, Qianying ZHAO, Jing PENG, Min WEI, Yushun ZHANG, Xing ZHANG Clicked:2905 Download:2265 Cited:0 <Full Text> <PPT> 364 Frontiers of Information Technology & Electronic Engineering 2024 Vol.25 No.5 P.713-727 DOI:10.1631/FITEE.2300122
18	Dynamic parameterized learning for unsupervised domain adaptation Author(s):Runhua JIANG, Yahong HAN Clicked:2490 Download:9947 Cited:0 <Full Text> Frontiers of Information Technology & Electronic Engineering 2023 Vol.24 No.11 P.1616-1632 DOI:10.1631/FITEE.2200631
19	Transfer learning with a spatiotemporal graph convolution network for city flow prediction Author(s):Binkun LIU, Yu KANG, Yang CAO, Yunbo ZHAO, Zhenyi XU Clicked:1878 Download:1221 Cited:0 <Full Text> <PPT> 435 Frontiers of Information Technology & Electronic Engineering 2025 Vol.26 No.1 P.79-92 DOI:10.1631/FITEE.2300571
20	Frequency-learning adversarial networks based on transfer learning for cross-scenario signal modulation classification Author(s):Qinyan MA, Jing XIAO, Zeqi SHAO, Duona ZHANG, Yufeng WANG, Wenrui DING Clicked:1121 Download:977 Cited:0 <Full Text> Frontiers of Information Technology & Electronic Engineering 2025 Vol.26 No.5 P.816-832 DOI:10.1631/FITEE.2400080
21	EPDI-transfer learning method for highly accurate prediction of lithium diffusion barriers on TMD surfaces Author(s):Jian CHEN^1,², Yao KANG^1,², Xudong WANG^1,², Hao HUANG¹, Man YAO^1,² Clicked:351 Download:446 Cited:0 <Full Text> Journal of Zhejiang University Science A In Press DOI:
22	Online transfer learning with an MLP-assisted graph convolutional network for traffic flow forecasting: a solution for edge intelligent devices Author(s):Jingru SUN¹, Chendingying LU¹, Yichuang SUN², Hongbo JIANG¹, Zhu XIAO¹ Clicked:285 Download:219 Cited:0 <Full Text> Frontiers of Information Technology & Electronic Engineering In Press DOI:

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