Zhiqiang Xu

Variational Bayes for Federated Continual Learning

2024 · arXiv (Cornell University)

Federated continual learning (FCL) has received increasing attention due to its potential in handling real-world streaming data, characterized by evolving data distributions and varying client classes over time. The constraints of storage limitations and privacy …

Rethinking Personalized Federated Learning from Knowledge Perspective

2024

Personalized federated learning (PFL) is a variant of federation learning, which improves the model performance of each participant through collaborative training while providing a customized local model that meets their unique needs. Balancing global (general) …

LAMP: Learnable Meta-Path Guided Adversarial Contrastive Learning for Heterogeneous Graphs

2024 · arXiv (Cornell University)

Heterogeneous graph neural networks (HGNNs) have significantly propelled the information retrieval (IR) field. Still, the effectiveness of HGNNs heavily relies on high-quality labels, which are often expensive to acquire. This challenge has shifted attention towards …

Online Parallel Multi-Task Relationship Learning via Alternating Direction Method of Multipliers

2024 · arXiv (Cornell University)

Online multi-task learning (OMTL) enhances streaming data processing by leveraging the inherent relations among multiple tasks. It can be described as an optimization problem in which a single loss function is defined for multiple tasks. …