Structured low-rank approximation (SLRA) is a mathematical framework that seeks to approximate a given data matrix by another matrix of lower rank while preserving intrinsic structural properties.

Abstract: It remains a challenging to capture inter-variable correlations in time series forecasting (TSF), which leads researchers to focus more on channel-independent TSF methods. However, it is ...