- [pdf] [arXiv]
Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition
We study the problem of tensor robust principal component analysis (TRPCA), that aims to separate an underlying low-multilinear-rank tensor and a sparse outlier tensor from their sum. In this work, we propose a fast non-convex algorithm, coined Robust Tensor CUR (RTCUR), for large-scale TRPCA problems. RTCUR considers a framework of alternating projections and utilizes the recently developed tensor Fiber CUR decomposition to dramatically lower its computational complexity. The speed advantage of RTCUR is empirically verified against the state-of-the-art on both synthetic and real-world datasets.