Consensus problems in time-varying networks are studied in this paper. We consider two cases. In the first case, the networks are basically connected and the conditions for reaching consensus are described by means of the algebraic properties of connectivity for network graph. In the second case, the networks are possibly disconnected all time. A concept called integral connectivity of networks...

Tensors are effective representations for complex and time-varying networks. The factorization of a tensor provides a high-quality low-rank compact basis for each dimension of the tensor, which facilitates the interpretation of important structures of the represented data. Many existing tensor factorization (TF) methods assume there is one tensor that needs to be decomposed to low-rank factors....

The varying coefficient models are very important tool to explore the dynamic pattern in many scientific areas, such as economics, finance, politics, epidemiology, medical science, ecology and so on. They are natural extensions of classical parametric models with good interpretability and are becoming more and more popular in data analysis. Thanks to their flexibility and interpretability, in t...