Change Point Detection in Dynamic Networks via Regularized Tensor Decomposition

Dynamic network captures time-varying interactions among multiple entities at different time points, and detecting its structural change points is of central interest. This article proposes a novel…

Covariate-Assisted Community Detection in Multi-Layer Networks

Communities in multi-layer networks consist of nodes with similar connectivity patterns across all layers. This article proposes a tensor-based community detection method in multi-layer networks, w…

Community Detection in General Hypergraph Via Graph Embedding

Conventional network data have largely focused on pairwise interactions between two entities, yet multi-way interactions among multiple entities have been frequently observed in real-life hypergrap…

Directed Community Detection With Network Embedding

Community detection in network data aims at grouping similar nodes sharing certain characteristics together. Most existing methods focus on detecting communities in undirected networks, where simil…

Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via…

Directed acyclic graph (DAG) models are widely used to represent casual relationships among random variables in many application domains. This article studies a special class of non-Gaussian DAG mo…

Embedding Learning

Numerical embedding has become one standard technique for processing and analyzing unstructured data that cannot be expressed in a predefined fashion. It stores the main characteristics of data by …

Scalable Collaborative Ranking for Personalized Prediction

Personalized prediction presents an important yet challenging task, which predicts user-specific preferences on a large number of items given limited information. It is often modeled as certain rec…

Classification with unstructured predictors and an application to sentiment a…