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In this PhD thesis, we give a new geometric approach to higher Teichm\"uller theory. In particular we construct a geometric structure on surfaces, generalizing the complex structure, and we explore its link to Hitchin components. The…

Differential Geometry · Mathematics 2020-07-02 Alexander Thomas

We produce a decomposition of the parameter space of the $A$-hypergeometric system associated to a projective monomial curve as a union of an arrangement of lines and its complement, in such a way that the analytic behavior of the solutions…

Algebraic Geometry · Mathematics 2015-12-03 Christine Berkesch Zamaere , Jens Forsgård , Laura Felicia Matusevich

Modelling compositionality has been a longstanding area of research in the field of vector space semantics. The categorical approach to compositionality maps grammar onto vector spaces in a principled way, but comes under fire for requiring…

Computation and Language · Computer Science 2019-01-31 Martha Lewis

The situation of two independent observers conducting measurements on a joint quantum system is usually modelled using a Hilbert space of tensor product form, each factor associated to one observer. Correspondingly, the operators describing…

Mathematical Physics · Physics 2009-06-25 V. B. Scholz , R. F. Werner

This thesis proposes a combinatorial generalization of a nilpotent operator on a vector space. The resulting object is highly natural, with basic connections to a variety of fields in pure mathematics, engineering, and the sciences. For the…

Category Theory · Mathematics 2020-04-21 Gregory Henselman-Petrusek

Generalizations and variations of the fundamental lemma by Willems et al. are an active topic of recent research. In this note, we explore and formalize the links between kernel regression and some known nonlinear extensions of the…

Systems and Control · Electrical Eng. & Systems 2024-09-16 Oleksii Molodchyk , Timm Faulwasser

Any applied mathematical model contains parameters. The paper proposes to use kernel learning for the parametric analysis of the model. The approach consists in setting a distribution on the parameter space, obtaining a finite training…

Optimization and Control · Mathematics 2025-01-27 Vladimir Norkin , Alois Pichler

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

The paper discusses a series of results concerning reproducing kernel Hilbert spaces, related to the factorization of their kernels. In particular, it is proved that for a large class of spaces isometric multipliers are trivial. One also…

Functional Analysis · Mathematics 2016-05-10 Rani Kumari , Jaydeb Sarkar , Srijan Sarkar , Dan Timotin

The characteristic varieties of a space are the jump loci for homology of rank 1 local systems. The way in which the geometry of these varieties may vary with the characteristic of the ground field is reflected in the homology of finite…

Algebraic Geometry · Mathematics 2014-06-13 Graham Denham , Alexander I. Suciu

In this paper we investigate the problem of estimating the regression function in models with correlated observations. The data is obtained from several experimental units each of them forms a time series. We propose a new estimator based…

Statistics Theory · Mathematics 2019-06-13 Djihad Benelmadani , Karim Benhenni , Sana Louhichi

The structure properties of multidimensional Delsarte transmutation operators in parametirc functional spaces are studied by means of differential-geometric tools. It is shown that kernels of the corresponding integral operator expressions…

Mathematical Physics · Physics 2007-05-23 J. Golenia , Y. A. Prykarpatsky , A. M. Samoilenko , A. K. Prykarpatsky

We propose a kernel method to identify finite mixtures of nonparametric product distributions. It is based on a Hilbert space embedding of the joint distribution. The rank of the constructed tensor is equal to the number of mixture…

Machine Learning · Computer Science 2013-09-27 Eleni Sgouritsa , Dominik Janzing , Jonas Peters , Bernhard Schoelkopf

In this article, the reproducing kernel Hilbert space [0, 1] is employed for solving a class of third-order periodic boundary value problem by using fitted reproducing kernel algorithm. The reproducing kernel function is built to get fast…

Numerical Analysis · Mathematics 2017-04-18 Asad Freihat , Radwan Abu-Gdairi , Hammad Khalil , Eman Abuteen , Mohammed Al-Smadi , Rahmat Ali Khan

This paper introduces a computational framework to identify nonlinear input-output operators that fit a set of system trajectories while satisfying incremental integral quadratic constraints. The data fitting algorithm is thus regularized…

Optimization and Control · Mathematics 2021-10-25 Henk J. van Waarde , Rodolphe Sepulchre

Elaborating on our joint work with Abramsky in quant-ph/0402130 we further unravel the linear structure of Hilbert spaces into several constituents. Some prove to be very crucial for particular features of quantum theory while others…

Quantum Physics · Physics 2007-05-23 Bob Coecke

This paper studies the construction of a refinement kernel for a given operator-valued reproducing kernel such that the vector-valued reproducing kernel Hilbert space of the refinement kernel contains that of the given one as a subspace.…

Machine Learning · Computer Science 2011-02-08 Yuesheng Xu , Haizhang Zhang , Qinghui Zhang

In this paper we consider several problems of joint similarity to tuples of bounded linear operators in noncommutative polydomains and varieties associated with sets of noncommutative polynomials. We obtain analogues of classical results…

Functional Analysis · Mathematics 2014-12-05 Gelu Popescu

The study presents a vector-valued extension of the classical Mercer theorem within the framework of reproducing kernel Hilbert spaces defined over Kaplansky-Hilbert modules associated with the algebra of essentially bounded measurable…

Functional Analysis · Mathematics 2025-11-24 A. Arziev , K. Kudaybergenov. P. Orinbaev

In this work, we study the Dirichlet problem associated with a strongly coupled system of nonlocal equations. The system of equations comes from a linearization of a model of peridynamics, a nonlocal model of elasticity. It is a nonlocal…

Analysis of PDEs · Mathematics 2018-05-24 Moritz Kassmann , Tadele Mengesha , James Scott