We propose a new approach to modeling time-varying relational data such as e-mail transactions based on a dynamic extension of matrix factorization. To estimate effectively the true relationships behind a sequence of noise-corrupted relational matrices, their dynamic evolutions are modeled in a space of low-rank matrices. The observed matrices are assumed as to be sampled from an exponential fa...

This paper introduces a novel class of Bayesian models for multivariate time series analysis based on a synthesis of dynamic linear models and graphical models. The synthesis uses sparse graphical modelling ideas to introduce structured, conditional independence relationships in the time-varying, cross-sectional covariance matrices of multiple time series. We define this new class of models and...

Collaborative filtering algorithms generally rely on the assumption that user preference patterns remain stationary. However, real-world relational data are seldom stationary. User preference patterns may change over time, giving rise to the requirement of designing collaborative filtering systems capable of detecting and adapting to preference pattern shifts. Motivated by this observation, in ...

A key problem in cooperative control is the convergence to a common value of the systems, which is called the consensus or agreement problem. Among recent results in cooperative control of multi-agent dynamic systems, the method used can be categorized in either graph theory or matrix theory based techniques, and the agent dynamics is either a single/double integrator or a linear system transfo...

Intelligent Transportation Systems (ITS) have received a great deal of attention in overcoming traffic-associated problems by implementing online traffic management, which inevitably depends on the accurate dynamic traffic demand. Dynamic Traffic Demand is a fundamental input for simulation-based Dynamic Traffic Assignment (DTA) models to describe and predict traffic conditions on the network o...

Approaches for regulated fluid secretion, which typically rely on fluid encapsulation and release from a shelled compartment, do not usually allow a fine continuous modulation of secretion, and can be difficult to adapt for monitoring or function-integration purposes. Here, we report self-regulated, self-reporting secretion systems consisting of liquid-storage compartments in a supramolecular p...