5 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.LG2024
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
Jiayi Wang, Shiqiang Wang, Rong-Rong Chen +1
In federated learning (FL), data heterogeneity is the main reason that existing theoretical analyses are pessimistic about the convergence rate. In particular, for many FL algorith…
cs.CV2022★ 4 cited
Few-shot Fine-grained Image Classification via Multi-Frequency Neighborhood and Double-cross Modulation
Hegui Zhu, Zhan Gao, Jiayi Wang +2
Traditional fine-grained image classification typically relies on large-scale training samples with annotated ground-truth. However, some sub-categories have few available samples…
cs.LG2020★ 5 cited
Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD
Jiayi Wang, Shiqiang Wang, Rong-Rong Chen +1
Hierarchical SGD (H-SGD) has emerged as a new distributed SGD algorithm for multi-level communication networks. In H-SGD, before each global aggregation, workers send their updated…