テンソル分解の基礎と応用（MIRU2022チュートリアル）

Signal Processing Society Magazine Best Paper Award (ICASSPにて) A. Cichocki (Skoltech) L. De Lathauwer (KULeuven) 19 テンソル分解のパイオニアと重要な文献 Sidiropoulosらのレビュー論文 Tensor Decomposition for Signal Processing and Machine Learning Sidiropoulos, IEEE TSP, 2017 [pdf] Cichockiらの書籍 Tensor Networks for Dimensionality Reduction and Large-Scale Optimization: Part 1 [link], Part 2 [pdf] Cichocki, Foundations and Trends in Machine Learning, 2016 [link] N. Sidiropoulos (Univ. of Virginia) 20 宣伝 Book chapterを書きました Tensors for Data Processing, Elsevier, 2021 [link] 目次 1章 Tensor decompositions: Computations, applications, and challenges 2章 Transform-based tensor SVD in multidimensional image recovery 3章 Partensor 4章 A Riemannian approach to low-rank tensor learning 5章 Generalized thresholding for low-rank tensor recovery 6章 Tensor principal component analysis 7章 Tensors for deep learning theory 8章 Tensor network algorithms for image classification 9章 High-performance TD for compressing and accelerating DNN 10章 Coupled tensor decomposition for data fusion 11章 Tensor methods for low-level vision T. Yokota, CF.