no code implementations • 2 Feb 2024 • Guangfeng Yan, Tan Li, Yuanzhang Xiao, Congduan Li, Linqi Song
To address the communication bottleneck challenge in distributed learning, our work introduces a novel two-stage quantization strategy designed to enhance the communication efficiency of distributed Stochastic Gradient Descent (SGD).
no code implementations • 23 Aug 2022 • Sichun Luo, Yuanzhang Xiao, Yang Liu, Congduan Li, Linqi Song
Federated recommendations leverage the federated learning (FL) techniques to make privacy-preserving recommendations.
1 code implementation • IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW) 2022 • Jingyuan Zhou, Chaktou Leong, Minyi Lin, Wantong Liao, Congduan Li
Therefore, we propose a task-adaptive attention module to enable the network to restore images with multiple degradation factors.
1 code implementation • 16 Jul 2019 • Mengwei Yang, Linqi Song, Jie Xu, Congduan Li, Guozhen Tan
Our proposed federated XGBoost algorithm incorporates data aggregation and sparse federated update processes to balance the tradeoff between privacy and learning performance.