Federated learning is a decentralized and privacy-preserving technique t...
To improve the robustness of graph neural networks (GNN), graph structur...
Graph convolutional networks (GCN) are viewed as one of the most popular...
Graph convolutional network (GCN) is a powerful model studied broadly in...
This paper considers the partially functional linear model (PFLM) where ...
Communication efficiency and robustness are two major issues in modern
d...
This paper aims at studying the sample complexity of graph convolutional...
This paper analyzes a new regularized learning scheme for high dimension...
Forecasting stock market direction is always an amazing but challenging
...
Variable selection is central to high-dimensional data analysis, and var...
We consider a distributed estimation of the double-penalized least squar...