no code implementations • 10 Dec 2023 • Rui Ye, Yaxin Du, Zhenyang Ni, Siheng Chen, Yanfeng Wang
FedCOG consists of two key components at the client side: complementary data generation, which generates data extracted from the shared global model to complement the original dataset, and knowledge-distillation-based model training, which distills knowledge from global model to local model based on the generated data to mitigate over-fitting the original heterogeneous dataset.
no code implementations • 14 Oct 2022 • Rui Ye, Zhenyang Ni, Chenxin Xu, Jianyu Wang, Siheng Chen, Yonina C. Eldar
This method attempts to mitigate the negative effects of data heterogeneity in FL by aligning each client's feature space.
no code implementations • 20 Jul 2022 • Yiqi Zhong, Zhenyang Ni, Siheng Chen, Ulrich Neumann
In this work, we re-introduce this information as a new type of input data for trajectory forecasting systems: the local behavior data, which we conceptualize as a collection of location-specific historical trajectories.
1 code implementation • CVPR 2022 • Chenxin Xu, Maosen Li, Zhenyang Ni, Ya zhang, Siheng Chen
From the aspect of interaction capturing, we propose a trainable multiscale hypergraph to capture both pair-wise and group-wise interactions at multiple group sizes.