1 citations · 1 across the 9 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2024
GPFL: A Gradient Projection-Based Client Selection Framework for Efficient Federated Learning
Shijie Na, Yuzhi Liang, Siu-Ming Yiu
Federated learning client selection is crucial for determining participant clients while balancing model accuracy and communication efficiency. Existing methods have limitations in…
cs.LG2024
Deep Efficient Private Neighbor Generation for Subgraph Federated Learning
Ke Zhang, Lichao Sun, Bolin Ding +2
Behemoth graphs are often fragmented and separately stored by multiple data owners as distributed subgraphs in many realistic applications. Without harming data privacy, it is natu…
cs.LG2022★ 1 cited
Deep Multiple Instance Learning For Forecasting Stock Trends Using Financial News
Yiqi Deng, Siu Ming Yiu
A major source of information can be taken from financial news articles, which have some correlations about the fluctuation of stock trends. In this paper, we investigate the influ…