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We develop algebraic methods for computations with tensor data. We give 3 applications: extracting features that are invariant under the orthogonal symmetries in each of the modes, approximation of the tensor spectral norm, and…

Representation Theory · Mathematics 2021-01-19 Neriman Tokcan , Jonathan Gryak , Kayvan Najarian , Harm Derksen

The formalisation of mathematics is continuing rapidly, however combinatorics continues to present challenges to formalisation efforts, such as its reliance on techniques from a wide range of other fields in mathematics. This paper presents…

Logic in Computer Science · Computer Science 2024-01-08 Chelsea Edmonds , Lawrence C. Paulson

Scientific computations or measurements may result in huge volumes of data. Often these can be thought of representing a real-valued function on a high-dimensional domain, and can be conceptually arranged in the format of a tensor of high…

Numerical Analysis · Mathematics 2019-09-24 Mike Espig , Wolfgang Hackbusch , Alexander Litvinenko , Hermann G. Matthies , Elmar Zander

We investigate the canonicity of inequalities of the intuitionistic mu-calculus. The notion of canonicity in the presence of fixed point operators is not entirely straightforward. In the algebraic setting of canonical extensions we examine…

Logic · Mathematics 2014-08-28 Willem Conradie , Andrew Craig

We introduce a notion of signature whose sorts form a direct category, and study computads for such signatures. Algebras for such a signature are presheaves with an interpretation of every function symbol of the signature, and we describe…

Category Theory · Mathematics 2024-11-06 Ioannis Markakis

The tensor decomposition addressed in this paper may be seen as a generalisation of Singular Value Decomposition of matrices. We consider general multilinear and multihomogeneous tensors. We show how to reduce the problem to a truncated…

Algebraic Geometry · Mathematics 2012-10-17 Alessandra Bernardi , Jerome Brachat , Pierre Comon , Bernard Mourrain

The classical number system encodes magnitude using a single scalar value whose sign positive or negative has remained conceptually unchanged for centuries. This work introduces Multisign Algebra, a mathematical generalization of the sign…

Rings and Algebras · Mathematics 2025-12-18 Sebastián Aliaga-Rojas , Pamela Landero-Sepúlveda , Mario Inostroza-Ponta

Tensors play a pivotal role in the realms of science and engineering, particularly in the realms of data analysis, machine learning, and computational mathematics. The process of unfolding a tensor into matrices, commonly known as tensor…

Rings and Algebras · Mathematics 2023-11-28 Shih-Yu Chang

We describe a type system for the linear-algebraic $\lambda$-calculus. The type system accounts for the linear-algebraic aspects of this extension of $\lambda$-calculus: it is able to statically describe the linear combinations of terms…

Logic in Computer Science · Computer Science 2017-05-12 Pablo Arrighi , Alejandro Díaz-Caro , Benoît Valiron

Recently, we have developed an efficient generic partition refinement algorithm, which computes behavioural equivalence on a state-based system given as an encoded coalgebra, and implemented it in the tool CoPaR. Here we extend this to a…

Data Structures and Algorithms · Computer Science 2022-11-10 Hans-Peter Deifel , Stefan Milius , Thorsten Wißmann

Some idea, which leads to a non-trivial solution of the quantum four-simplex equation, is exposed in this paper. We call this idea "pentagonal algebra". Few examples of the realisation of this idea are given here, and thus few examples of…

Mathematical Physics · Physics 2024-07-29 Sergey Sergeev

This note shows how quantum entanglement may be simulated in classical computing. The simulated entanglement protocol is implemented using oblivious transfer in the simplest case and other many-to-one mappings in more general cases. For the…

Quantum Physics · Physics 2013-01-11 Subhash Kak

Tensor diagonalization means transforming a given tensor to an exactly or nearly diagonal form through multiplying the tensor by non-orthogonal invertible matrices along selected dimensions of the tensor. It is generalization of approximate…

Numerical Analysis · Computer Science 2016-07-04 Petr Tichavsky , Anh Huy Phan , Andrzej Cichocki

Some basic ideas of the Refined Algebraic Quantization scheme are outlined at an intuitive level, using a class of simple models with a single wave equation as quantum constraint. In addition, hints are given how the scheme is applied to…

General Relativity and Quantum Cosmology · Physics 2011-04-15 Franz Embacher

The problem of Knowledge Base Completion can be framed as a 3rd-order binary tensor completion problem. In this light, the Canonical Tensor Decomposition (CP) (Hitchcock, 1927) seems like a natural solution; however, current implementations…

Machine Learning · Statistics 2018-06-20 Timothée Lacroix , Nicolas Usunier , Guillaume Obozinski

Modern language models represent probability distributions over character strings as distributions over (shorter) token strings derived via a deterministic tokenizer, such as byte-pair encoding. While this approach is highly effective at…

Conventional canonical quantization procedures directly link various c-number and q-number quantities. Here, we advocate a different association of classical and quantum quantities that renders classical theory a natural subset of quantum…

Quantum Physics · Physics 2014-03-25 John R. Klauder

We present RandomizedCCA, a randomized algorithm for computing canonical analysis, suitable for large datasets stored either out of core or on a distributed file system. Accurate results can be obtained in as few as two data passes, which…

Machine Learning · Statistics 2014-11-14 Paul Mineiro , Nikos Karampatziakis

We introduce a new OpenMath content dictionary, named tensor1, containing symbols for the expression of tensor formulas. These symbols support the expression of non-Cartesian coordinates and invariant, multilinear expressions in the context…

Mathematical Software · Computer Science 2010-05-25 Joseph B. Collins

Squared tensor networks (TNs) and their generalization as parameterized computational graphs -- squared circuits -- have been recently used as expressive distribution estimators in high dimensions. However, the squaring operation introduces…

Machine Learning · Computer Science 2025-01-22 Lorenzo Loconte , Antonio Vergari