Standout Papers

Model Pruning Enables Efficient Federated Learning on Edge Devices 2022 2026 2023 2024226
  1. Model Pruning Enables Efficient Federated Learning on Edge Devices (2022)
    Yuang Jiang, Shiqiang Wang et al. IEEE Transactions on Neural Networks and Learning Systems

Immediate Impact

41 standout
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Citing Papers

Edge deep learning in computer vision and medical diagnostics: a comprehensive survey
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From challenges and pitfalls to recommendations and opportunities: Implementing federated learning in healthcare
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2 intermediate papers

Works of Víctor Valls being referenced

Model Pruning Enables Efficient Federated Learning on Edge Devices
2022 Standout

Author Peers

Author Last Decade Papers Cites
Víctor Valls 110 104 176 15 298
Bong Jun Ko 93 70 176 10 274
Yuang Jiang 71 52 176 9 265
Dian Shi 130 99 110 12 279
Xiaomin Ouyang 63 52 190 18 285
Hongbin Zhu 104 99 182 32 303
Zhiyuan Wang 105 46 198 27 283
Jiahao Ding 59 50 186 22 263
Wenjing Zhang 68 64 117 25 224
Shuo Wang 67 47 130 17 242
Jiangming Jin 104 60 165 11 279

All Works

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2026