Company financial risk is ubiquitous and early risk assessment for listed companies can
avoid considerable losses. Traditional methods mainly focus on the financial statements of …

Graphs consisting of vocal nodes (" the vocal minority") and silent nodes (" the silent
majority"), namely VS-Graph, are ubiquitous in the real world. The vocal nodes tend to have …

The study of feature propagation at initialization in neural networks lies at the root of
numerous initialization designs. An assumption very commonly made in the field states that …

This work simultaneously considers the discriminability and transferability properties of deep
representations in the typical supervised learning task, ie, image classification. By a …

In recent years, the emergence and development of third-party platforms have greatly
facilitated the growth of the Online to Offline (O2O) business. However, the large amount of …

Graph Neural Networks (GNNs) have become essential in interpreting relational data across
various domains, yet, they often struggle to generalize to unseen graph data that differs …

Financial market participants frequently rely on numerous business relationships to make
investment decisions. Investors can learn about potential risks and opportunities associated …

Learning rate is one of the most important hyper-parameters that has significant influence for
neural network training. Learning rate schedules are widely used in real practice to adjust …

Federated learning (FL) has been proposed to enable distributed learning on Artificial
Intelligence Internet of Things (AIoT) devices with guarantees of high-level data privacy …

This study comes as a timely response to mounting criticism of the information bottleneck
(IB) theory, injecting fresh perspectives to rectify misconceptions and reaffirm its validity …