2 citations · 4 across the 3 of their papers we have counts for
7 papers
Personalized Federated Learning with Hidden Information on Personalized Prior
Mingjia Shi, Yuhao Zhou, Qing Ye +1
Federated learning (FL for simplification) is a distributed machine learning technique that utilizes global servers and collaborative clients to achieve privacy-preserving global m…
DeFTA: A Plug-and-Play Decentralized Replacement for FedAvg
Yuhao Zhou, Minjia Shi, Yuxin Tian +2
Federated learning (FL) is identified as a crucial enabler for large-scale distributed machine learning (ML) without the need for local raw dataset sharing, substantially reducing…
Fuse Local and Global Semantics in Representation Learning
Yuchi Zhao, Yuhao Zhou
We propose Fuse Local and Global Semantics in Representation Learning (FLAGS) to generate richer representations. FLAGS aims at extract both global and local semantics from images…
LANA: Towards Personalized Deep Knowledge Tracing Through Distinguishable Interactive Sequences
Yuhao Zhou, Xihua Li, Yunbo Cao +3
In educational applications, Knowledge Tracing (KT), the problem of accurately predicting students' responses to future questions by summarizing their knowledge states, has been wi…
Communication-Efficient Federated Learning with Compensated Overlap-FedAvg
Yuhao Zhou, Ye Qing, Jiancheng Lv
Petabytes of data are generated each day by emerging Internet of Things (IoT), but only few of them can be finally collected and used for Machine Learning (ML) purposes due to the…
HPSGD: Hierarchical Parallel SGD With Stale Gradients Featuring
Yuhao Zhou, Qing Ye, Hailun Zhang +1
While distributed training significantly speeds up the training process of the deep neural network (DNN), the utilization of the cluster is relatively low due to the time-consuming…