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
Noisy Nonnegative Tucker Decomposition with Sparse Factors and Missing Data
Xiongjun Zhang, Michael K. Ng
Tensor decomposition is a powerful tool for extracting physically meaningful latent factors from multi-dimensional nonnegative data, and has been an increasing interest in a variet…