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Given a finite family of compact subsets of the complex plane we propose a certificate of mutual non-overlapping with respect to area measure. The criterion is stated as a couple of positivity conditions imposed on a four argument…

Spectral Theory · Mathematics 2024-11-22 Bjorn Gustafsson , Mihai Putinar

A universal kernel is constructed whose sections approximate any causal and time-invariant filter in the fading memory category with inputs and outputs in a finite-dimensional Euclidean space. This kernel is built using the reservoir…

Machine Learning · Computer Science 2025-09-05 Lukas Gonon , Lyudmila Grigoryeva , Juan-Pablo Ortega

Despite the popularity of low-rank matrix completion, the majority of its theory has been developed under the assumption of random observation patterns, whereas very little is known about the practically relevant case of non-random…

Machine Learning · Computer Science 2023-02-24 Manolis C. Tsakiris

Helmke et al. have recently given a formula for the number of reachable pairs of matrices over a finite field. We give a new and elementary proof of the same formula by solving the equivalent problem of determining the number of so called…

Combinatorics · Mathematics 2016-03-18 Samrith Ram

In this article, a characterization of the class of Herglotz-Nevanlinna functions in $n$ variables is given in terms of an integral representation. Furthermore, alternative conditions on the measure appearing in this representation are…

Complex Variables · Mathematics 2019-09-24 Annemarie Luger , Mitja Nedic

We address the problem of filling missing entries in a kernel Gram matrix, given a related full Gram matrix. We attack this problem from the viewpoint of regression, assuming that the two kernel matrices can be considered as explanatory…

Quantitative Methods · Quantitative Biology 2011-11-10 Yoshihiro Yamanishi , Jean-Philippe Vert

This work proposed kernel selection approaches for probabilistic classifiers based on features produced by the convolutional encoder of a variational autoencoder. Particularly, the developed methodologies allow the selection of the most…

Machine Learning · Computer Science 2025-08-05 Fábio Mendonça , Sheikh Shanawaz Mostafa , Fernando Morgado-Dias , Antonio G. Ravelo-García

In data science, individual observations are often assumed to come independently from an underlying probability space. Kernel matrices formed from large sets of such observations arise frequently, for example during classification tasks. It…

Machine Learning · Statistics 2026-05-27 Mikhail Lepilov

We propose new positive definite kernels for permutations. First we introduce a weighted version of the Kendall kernel, which allows to weight unequally the contributions of different item pairs in the permutations depending on their ranks.…

Machine Learning · Statistics 2018-06-13 Yunlong Jiao , Jean-Philippe Vert

We define a family of kernels for mixed continuous/discrete hierarchical parameter spaces and show that they are positive definite.

Machine Learning · Statistics 2013-10-23 Frank Hutter , Michael A. Osborne

We study the structure of nilpotent completely positive maps in terms of Choi-Kraus coefficients. We prove several inequalities, including certain majorization type inequalities for dimensions of kernels of powers of nilpotent completely…

Operator Algebras · Mathematics 2013-10-03 B V Rajarama Bhat , Nirupama Mallick

Kernel approximation via nonlinear random feature maps is widely used in speeding up kernel machines. There are two main challenges for the conventional kernel approximation methods. First, before performing kernel approximation, a good…

Machine Learning · Statistics 2015-03-16 Felix X. Yu , Sanjiv Kumar , Henry Rowley , Shih-Fu Chang

We show that a nef line bundle on a proper scheme over an excellent base is semiample if and only if it is semiample after restricting to characteristic zero and to positive characteristic. In the process of the proof, we provide a…

Algebraic Geometry · Mathematics 2021-06-14 Jakub Witaszek

We give a self-contained derivation of the Stinespring and Kraus structure theorems for completely positive maps using only scalar positive-definite kernels.

Functional Analysis · Mathematics 2025-12-02 James Tian

Solving the intricate quantum behavior of interacting particles is key to unlocking the mysteries of condensed matter, but capturing their complex correlations across different scales remains a monumental challenge. We introduce a neural…

A theorem of Kaplansky asserts that a semigroup of matrices with entries from a field whose members all have singleton spectra is triangularizable. Indeed, Kaplansky's Theorem unifies well-known theorems of Kolchin and Levitzki on…

Rings and Algebras · Mathematics 2016-02-19 Heydar Radjavi , Bamdad R. Yahaghi

The kernel matrix used in kernel methods encodes all the information required for solving complex nonlinear problems defined on data representations in the input space using simple, but implicitly defined, solutions. Spectral analysis on…

Machine Learning · Computer Science 2020-10-26 Alexandros Iosifidis

It is known that the problem of deleting at most k vertices to obtain a proper interval graph (Proper Interval Vertex Deletion) is fixed parameter tractable. However, whether the problem admits a polynomial kernel or not was open. Here, we…

Data Structures and Algorithms · Computer Science 2015-03-20 Fedor V. Fomin , Saket Saurabh , Yngve Villanger

We call the solution of a kind of second order homogeneous partial differential equation as real kernel alpha-harmonic mappings. In this paper, the representation theorem, the Lipschitz continuity, the univalency and the related problems of…

Complex Variables · Mathematics 2024-01-22 Bo-Yong Long , Qi-Han Wang

We study the existence and uniqueness of the heat kernel on infinite, locally finite, connected graphs. For general graphs, a uniqueness criterion, shown to be optimal, is given in terms of the maximal valence on spheres about a fixed…

Spectral Theory · Mathematics 2008-04-24 Radoslaw K. Wojciechowski
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