This article presents communication-efficient approaches to federated learning (FL) for
resource-constrained devices with access to streaming data. In particular, we first propose a …

By integrating domain knowledge with labeled samples, informed machine learning has
been emerging to improve the learning performance for a wide range of applications …

We consider estimation under scenarios where the signals of interest exhibit change of
characteristics over time. In particular, we consider the continual learning problem where …

Privacy-preserving distributed distribution comparison measures the distance between the
distributions whose data are scattered across different agents in a distributed system and …

We revisit two fundamental decentralized optimization methods, Decentralized Gradient
Tracking (DGT) and Decentralized Gradient Descent (DGD), with multiple local updates. We …

Random feature (RF) has been widely used for node consistency in decentralized kernel
ridge regression (KRR). Currently, the consistency is guaranteed by imposing constraints on …