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We introduce and study the definition, main properties and applications of iterated twisted tensor products of algebras, motivated by the problem of defining a suitable representative for the product of spaces in noncommutative geometry. We…

Quantum Algebra · Mathematics 2016-08-16 P. Jara Martínez , J. López Peña , F. Panaite , F. Van Oystaeyen

There is a need in general relativity for a consistent and useful mathematical theory defining the multiplication of tensor distributions in a geometric (diffeomorphism invariant) way. Significant progress has been made through the concept…

General Relativity and Quantum Cosmology · Physics 2011-12-12 Jozef Skakala

In this paper we obtain asymptotic expansion for the geometric mean of the values of positive strongly multiplicative function $f$ satisfying $f(p)=\alpha(d)\,p^d+O(p^{d-\delta})$ for any prime $p$ with $d$ real and $\alpha(d),\delta>0$.

Number Theory · Mathematics 2023-06-22 Mehdi Hassani , Mohammadreza Esfandiari

4x4x3 absolutely nonsingular tensors are characterized by their determinant polynomial. Non-quivalence among absolutely nonsingular tensors with respect to a class of linear transformations, which do not chage the tensor rank,is studied. It…

Computing derivatives of tensor expressions, also known as tensor calculus, is a fundamental task in machine learning. A key concern is the efficiency of evaluating the expressions and their derivatives that hinges on the representation of…

Machine Learning · Computer Science 2020-10-08 Sören Laue , Matthias Mitterreiter , Joachim Giesen

We investigate the asymptotic properties of a kernel-type nonparametric estimator of the linear multiplier in models governed by a stochastic differential equation driven by a general Gaussian process.

Statistics Theory · Mathematics 2022-09-07 B. L. S. Prakasa Rao

In this paper, we propose a method for importing tensor index notation, including Einstein summation notation, into functional programming. This method involves introducing two types of parameters, i.e, scalar and tensor parameters, and…

Programming Languages · Computer Science 2018-08-31 Satoshi Egi

Linear regression without correspondences is the problem of performing a linear regression fit to a dataset for which the correspondences between the independent samples and the observations are unknown. Such a problem naturally arises in…

Machine Learning · Computer Science 2019-10-07 Manolis C. Tsakiris , Liangzu Peng , Aldo Conca , Laurent Kneip , Yuanming Shi , Hayoung Choi

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

The development of energy selective, photon counting X-ray detectors allows for a wide range of new possibilities in the area of computed tomographic image formation. Under the assumption of perfect energy resolution, here we propose a…

Computer Vision and Pattern Recognition · Computer Science 2015-06-16 Oguz Semerci , Ning Hao , Misha E. Kilmer , Eric L. Miller

We consider a version of geometric programming problem consisting in minimizing a function given by the maximum of finitely many log-Laplace transforms of discrete nonnegative measures on a Euclidean space. Under a coerciveness assumption,…

Optimization and Control · Mathematics 2025-06-04 Shmuel Friedland , Stéphane Gaubert

Formulating non-Abelian gauge theories as a tensor network is known to be challenging due to the internal degrees of freedom that result in the degeneracy in the singular value spectrum. In two dimensions, it is straightforward to 'trace…

High Energy Physics - Theory · Physics 2024-07-17 Atis Yosprakob

In this paper, we present the definition of generalized tensor function according to the tensor singular value decomposition (T-SVD) via the tensor T-product. Also, we introduce the compact singular value decomposition (T-CSVD) of tensors…

Numerical Analysis · Mathematics 2019-10-17 Yun Miao , Liqun Qi , Yimin Wei

The set of matrix tuples with invariant subspaces whose dimensions sum up to the dimension of the space, but which do not span the whole space form an algebraic hypersurface. We found the equation of this hypersurface. This generalizes…

Algebraic Geometry · Mathematics 2026-04-27 Tamás Bencze

We generalize the embedding formalism for conformal field theories to the case of general operators with mixed symmetry. The index-free notation encoding symmetric tensors as polynomials in an auxiliary polarization vector is extended to…

High Energy Physics - Theory · Physics 2015-09-03 Miguel S. Costa , Tobias Hansen

In this paper, we address the open problem (stated in Pennisi and Trovato, 1987. Int. J. Engng Sci., 25(8), 1059-1065) associated with the irreducibility of representations for isotropic functions. In particular, we prove that for isotropic…

General Mathematics · Mathematics 2022-07-21 M. H. B. M. Shariff

This work introduces a tensor-based method to perform supervised classification on spatiotemporal data processed in an echo state network. Typically when performing supervised classification tasks on data processed in an echo state network,…

Machine Learning · Computer Science 2017-08-25 Ashley Prater

Quadratic, second-order, non-local actions for tensor gauge fields transforming in arbitrary irreducible representations of the general linear group in D-dimensional Minkowski space are explicitly written in a compact form by making use of…

High Energy Physics - Theory · Physics 2008-11-26 Xavier Bekaert , Nicolas Boulanger

In this study, we explore the geometric construction of the Klein bottle and the real projective plane ($\mathrm{RP}^2$) within the framework of tensor networks, focusing on the implementation of crosscap and rainbow boundaries. Previous…

Strongly Correlated Electrons · Physics 2026-03-11 Haruki Shimizu , Atsushi Ueda

It has recently been shown that the tensor rank can be strictly submultiplicative under the tensor product, where the tensor product of two tensors is a tensor whose order is the sum of the orders of the two factors. The necessary upper…

Algebraic Geometry · Mathematics 2019-05-02 Matthias Christandl , Fulvio Gesmundo , Asger Kjærulff Jensen