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Tensor completion is a natural higher-order generalization of matrix completion where the goal is to recover a low-rank tensor from sparse observations of its entries. Existing algorithms are either heuristic without provable guarantees,…

Data Structures and Algorithms · Computer Science 2023-07-14 Allen Liu , Ankur Moitra

Classical spectral theory gives a complete description of a single normal operator, but it fails for noncommuting operators, where no canonical joint spectrum or simultaneous diagonalization exists. Existing approaches provide only partial…

Category Theory · Mathematics 2026-01-27 Shih-Yu Chang

We propose a new numerical algorithm for computing the tensor rank decomposition or canonical polyadic decomposition of higher-order tensors subject to a rank and genericity constraint. Reformulating this computational problem as a system…

Numerical Analysis · Mathematics 2024-07-02 Simon Telen , Nick Vannieuwenhoven

We develop new solvability methods for divergence form second order, real and complex, elliptic systems above Lipschitz graphs, with $L_2$ boundary data. The coefficients $A$ may depend on all variables, but are assumed to be close to…

Analysis of PDEs · Mathematics 2010-09-16 Pascal Auscher , Andreas Axelsson

We interpret tensors on a smooth manifold M as differential forms over a graded commutative algebra called the algebra of iterated differential forms over M. This allows us to put standard tensor calculus in a new differentially closed…

Differential Geometry · Mathematics 2010-05-05 A. M. Vinogradov , L. Vitagliano

This article presents a reformulation of the Theory of Functional Connections: a general methodology for functional interpolation that can embed a set of user-specified linear constraints. The reformulation presented in this paper exploits…

Numerical Analysis · Mathematics 2020-08-07 Carl Leake , Hunter Johnston , Daniele Mortari

The functional ANOVA, or Hoeffding decomposition, provides a principled framework for interpretability by decomposing a model prediction into main effects and higher-order interactions. For independent inputs, this classical decomposition…

Machine Learning · Statistics 2026-05-19 Baptiste Ferrere , Nicolas Bousquet , Fabrice Gamboa , Jean-Michel Loubes

Clifford geometric algebras of multivectors are treated in detail. These algebras are build over a graded space and exhibit a grading or multivector structure. The careful study of the endomorphisms of this space makes it clear, that…

High Energy Physics - Theory · Physics 2015-06-26 Bertfried Fauser

Noncommutative rational functions appeared in many contexts in system theory and control, from the theory of finite automata and formal languages to robust control and LMIs. We survey the construction of noncommutative rational functions,…

Rings and Algebras · Mathematics 2015-03-13 Dmitry S. Kaliuzhnyi-Verbovetskyi , Victor Vinnikov

The fine structures on the $S$-spectrum constitute a new research area that includes a class of functional calculi based on the $S$-spectrum and on integral transforms determined by the Fueter--Sce mapping theorem and the Cauchy formula for…

Functional Analysis · Mathematics 2026-03-17 Fabrizio Colombo , Antonino De Martino , Joao Marques Da Costa

The representation theory of tensor functions is a powerful mathematical tool for constitutive modeling of anisotropic materials. A major limitation of the traditional theory is that many point groups require fourth- or sixth-order…

Representation Theory · Mathematics 2026-03-13 Mohammad Madadi , Pu Zhang

In this article, we first study, in the framework of operator theory, Pusz and Woronowicz's functional calculus for pairs of bounded positive operators on Hilbert spaces associated with a homogeneous two-variable function on $[0,\infty)^2$.…

Functional Analysis · Mathematics 2021-05-21 Fumio Hiai , Yoshimichi Ueda , Shuhei Wada

Graph-based methods have been proposed as a unified framework for discrete calculus of local and nonlocal image processing methods in the recent years. In order to translate variational models and partial differential equations to a graph,…

Numerical Analysis · Mathematics 2018-12-10 Ronny Bergmann , Daniel Tenbrinck

In this work, we present tensor-based linear and nonlinear models for hyperspectral data classification and analysis. By exploiting principles of tensor algebra, we introduce new classification architectures, the weight parameters of which…

Computer Vision and Pattern Recognition · Computer Science 2018-12-26 Konstantinos Makantasis , Anastasios Doulamis , Nikolaos Doulamis , Antonis Nikitakis

This work establishes a systematic framework for operator construction in the non-relativistic effective field theory, incorporating both the three dimensional Euclidean symmetry and the internal symmetries. By employing double cover of the…

High Energy Physics - Phenomenology · Physics 2026-02-13 Yong-Kang Li , Yi-Ning Wang , Jiang-Hao Yu

As low-rank modeling has achieved great success in tensor recovery, many research efforts devote to defining the tensor rank. Among them, the recent popular tensor tubal rank, defined based on the tensor singular value decomposition…

Computer Vision and Pattern Recognition · Computer Science 2018-12-04 Yu-Bang Zheng , Ting-Zhu Huang , Xi-Le Zhao , Tai-Xiang Jiang , Teng-Yu Ji , Tian-Hui Ma

We state a generalization of the Connes-Tretkoff-Moscovici Rearrangement Lemma and give a surprisingly simple (almost trivial) proof of it. Secondly, we put on a firm ground the multivariable functional calculus used implicitly in the…

Operator Algebras · Mathematics 2015-06-02 Matthias Lesch

The center of interest in this work are variational problems with integral functionals depending on special nonlocal gradients. The latter correspond to truncated versions of the Riesz fractional gradient, as introduced in [Bellido, Cueto &…

Analysis of PDEs · Mathematics 2023-04-18 Javier Cueto , Carolin Kreisbeck , Hidde Schönberger

Coupled tensor decomposition reveals the joint data structure by incorporating priori knowledge that come from the latent coupled factors. The tensor ring (TR) decomposition is invariant under the permutation of tensors with different mode…

Machine Learning · Computer Science 2020-11-10 Huyan Huang , Yipeng Liu , Ce Zhu

This paper presents a novel framework for high-dimensional nonlinear quantum computation that exploits tensor products of amplified vector and matrix encodings to efficiently evaluate multivariate polynomials. The approach enables the…

Quantum Physics · Physics 2025-10-01 Matthias Deiml , Daniel Peterseim