2 papers
math.ST2026
Sparse Tucker Decomposition and Graph Regularization for High-Dimensional Time Series Forecasting
Sijia Xia, Michael K. Ng, Xiongjun Zhang
Existing methods of vector autoregressive model for multivariate time series analysis make use of low-rank matrix approximation or Tucker decomposition to reduce the dimension of t…
cs.LG2024
Low-Rank Tensor Learning by Generalized Nonconvex Regularization
Sijia Xia, Michael K. Ng, Xiongjun Zhang
In this paper, we study the problem of low-rank tensor learning, where only a few of training samples are observed and the underlying tensor has a low-rank structure. The existing…