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An efficient decoding algorithm named `divided decoder' is proposed in this paper. Divided decoding can be combined with any decoder using QR-decomposition and offers different pairs of performance and complexity. Divided decoding provides…

Information Theory · Computer Science 2009-01-23 In Sook Park

We propose a new estimator, the quadratic form estimator, of the Kronecker product model for covariance matrices. We show that this estimator has good properties in the large dimensional case (i.e., the cross-sectional dimension $n$ is…

Statistics Theory · Mathematics 2020-12-23 Oliver B. Linton , Haihan Tang

We study the decomposability and the subdifferential of the tensor nuclear norm. Both concepts are well understood and widely applied in matrices but remain unclear for higher-order tensors. We show that the tensor nuclear norm admits a…

Optimization and Control · Mathematics 2026-03-17 Jiewen Guan , Bo Jiang , Zhening Li

We consider Gallai's graph Modular Decomposition theory for network analytics. On the one hand, by arguing that this is a choice tool for understanding structural and functional similarities among nodes in a network. On the other, by…

Discrete Mathematics · Computer Science 2018-12-04 Carenne Ludena , Miguel mendez , Nicolas Bolivar

This paper extends the class of ordinal regression models with a structured interpretation of the problem by applying a novel treatment of encoded labels. The net effect of this is to transform the underlying problem from an ordinal…

Machine Learning · Computer Science 2019-06-03 Niall Twomey , Rafael Poyiadzi , Callum Mann , Raúl Santos-Rodríguez

We construct the generalized version of covariant Z_3-graded differential calculus introduced by one of us (R.K.), and then extended to the case of arbitrary Z_N grading. Here our main purpose is to establish the recurrence formulae for the…

Quantum Algebra · Mathematics 2007-05-23 R. Kerner , B. Niemeyer

In this paper a new general approach is developed to construct and study Lebesgue type decompositions of linear operators $T$ in the Hilbert space setting. The new approach allows to introduce an essentially wider class of Lebesgue type…

Functional Analysis · Mathematics 2023-09-20 Seppo Hassi , Henk de Snoo

Second-order Recurrent Neural Networks (2RNNs) extend RNNs by leveraging second-order interactions for sequence modelling. These models are provably more expressive than their first-order counterparts and have connections to well-studied…

Machine Learning · Computer Science 2024-06-10 Maude Lizaire , Michael Rizvi-Martel , Marawan Gamal Abdel Hameed , Guillaume Rabusseau

In one of our former papers {\it Endomorphisms of the measure algebra of commutative hypergroups arXiv:2204.07499 we considered exponential monomials on hypergroups and higher order derivations of the corresponding measure algebra.…

Rings and Algebras · Mathematics 2022-09-20 Zywilla Fechner , Eszter Gselmann , László Székelyhidi

This work proposes a new model in the context of statistical theory of shape, based on the polar decomposition. The non isotropic noncentral elliptical shape distributions via polar decomposition is derived in the context of zonal…

Statistics Theory · Mathematics 2010-04-06 Jose A. Diaz-Garcia , Francisco J. Caro-Lopera

Quantum tomography, as a tool to probe foundational aspects of quantum mechanics, relies on extracting spin information from angular distributions. This is inherently a leading-order technique, ill-defined when higher-order corrections are…

High Energy Physics - Phenomenology · Physics 2025-09-11 J. A. Aguilar-Saavedra

We describe spatio-temporal random processes using linear mixed models. We show how many commonly used models can be viewed as special cases of this general framework and pay close attention to models with separable or product-sum…

Methodology · Statistics 2021-06-01 Michael Dumelle , Jay M. Ver Hoef , Claudio Fuentes , Alix Gitelman

We propose a mathematical framework that we call quantum, higher-order Fourier analysis. This generalizes the classical theory of higher-order Fourier analysis, which led to many advances in number theory and combinatorics. We define a…

Quantum Physics · Physics 2025-09-09 Kaifeng Bu , Weichen Gu , Arthur Jaffe

We consider the decomposition of bounded linear operators on Hilbert spaces in terms of functions forming frames. Similar to the singular-value decomposition, the resulting frame decompositions encode information on the structure and…

Numerical Analysis · Mathematics 2021-05-26 Simon Hubmer , Ronny Ramlau

Modeling with multidimensional arrays, or tensors, often presents a problem due to high dimensionality. In addition, these structures typically exhibit inherent sparsity, requiring the use of regularization methods to properly characterize…

Methodology · Statistics 2022-10-10 Daniel Spencer , Rajarshi Guhaniyogi , Russell Shinohara , Raquel Prado

In this contribution, we summarize and discuss recent theoretical progress on the Standard-Model calculation of joint polarized cross sections of massive multi-boson processes with fully leptonic decays. The topics include fixed-order…

High Energy Physics - Phenomenology · Physics 2025-09-25 Thi Nhung Dao , Duc Ninh Le

Low-rank decompositions to reduce the Coulomb operator to a pairwise form suitable for its quantum simulation are well-known in quantum chemistry, where the underlying basis functions are real-valued. We generalize the result of Motta…

Quantum Physics · Physics 2021-09-21 Michael P. Kaicher

A new method of estimating higher order perturbative coefficients is discussed. It exploits the rapid, asymptotic growth of perturbative coefficients and the information on the singularities in the complex Borel plane. A comparison with…

High Energy Physics - Phenomenology · Physics 2009-11-07 Kwang Sik Jeong , Taekoon Lee

The existence of decompositions of the nonlinear integrable systems not only permits us to establish so-called linear superposition solutions but also to derive new nonlinear integrable coupled systems. Restricting our attention to the…

Exactly Solvable and Integrable Systems · Physics 2022-05-18 Xiazhi Hao , S. Y. Lou

Seq2seq models have been shown to struggle with compositional generalisation, i.e. generalising to new and potentially more complex structures than seen during training. Taking inspiration from grammar-based models that excel at…

Computation and Language · Computer Science 2023-02-16 Matthias Lindemann , Alexander Koller , Ivan Titov
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