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We discuss a (i) quantized version of the Jordan decomposition theorem for a complex Borel measure on a compact Hausdorff space, namely, the more general problem of decomposing a general noncommutative kernel (a quantization of the standard…

Operator Algebras · Mathematics 2022-02-04 Joseph A. Ball , Gregory Marx , Victor Vinnikov

We study positive kernels on $X\times X$, where $X$ is a set equipped with an action of a group, and taking values in the set of $\mathcal A$-sesquilinear forms on a (not necessarily Hilbert) module over a $C^*$-algebra $\mathcal A$. These…

Operator Algebras · Mathematics 2021-01-22 Erkka Haapasalo , Juha-Pekka Pellonpää

We show that kernel-based quadrature rules for computing integrals can be seen as a special case of random feature expansions for positive definite kernels, for a particular decomposition that always exists for such kernels. We provide a…

Machine Learning · Computer Science 2015-11-10 Francis Bach

In this paper, we characterize all closed linear operators in a separable Hilbert space which are unitarily equivalent to an integral bi-Carleman operator in $L_2(R)$ with bounded and arbitrarily smooth kernel on $R^2$. In addition, we give…

Spectral Theory · Mathematics 2007-05-23 Igor M. Novitskii

We investigate the interaction between the existence of reproducing kernels on infinite-dimensional Hermitian vector bundles and the positivity properties of the corresponding bundles. The positivity refers to the curvature form of certain…

Functional Analysis · Mathematics 2014-02-04 Daniel Beltita , José E. Galé

Modeling videos and image-sets as linear subspaces has proven beneficial for many visual recognition tasks. However, it also incurs challenges arising from the fact that linear subspaces do not obey Euclidean geometry, but lie on a special…

Computer Vision and Pattern Recognition · Computer Science 2014-07-07 Mehrtash T. Harandi , Mathieu Salzmann , Sadeep Jayasumana , Richard Hartley , Hongdong Li

This paper investigates an iterative rank-one decomposition scheme for positive operators on a Hilbert space based on a residual-weighted congruence update. At each step the operator is compressed along a chosen unit vector while remaining…

Functional Analysis · Mathematics 2025-12-02 James Tian

This manuscript presents an algorithm for obtaining an approximation of a nonlinear high order control affine dynamical system. Controlled trajectories of the system are leveraged as the central unit of information via embedding them in…

Optimization and Control · Mathematics 2026-01-23 Moad Abudia , Tejasvi Channagiri , Joel A. Rosenfeld , Rushikesh Kamalapurkar

Kernel methods approximate nonlinear maps in a data-driven manner by projecting the target map onto a finite-dimensional Hilbert space called the solution space. Traditionally, this space is a subspace of a fixed ambient reproducing kernel…

Numerical Analysis · Mathematics 2026-01-30 Tamás Dózsa , Andrea Angino , Zoltán Szabó , József Bokor , Matthias Voigt

This survey contains a selection of topics unified by the concept of positive semi-definiteness (of matrices or kernels), reflecting natural constraints imposed on discrete data (graphs or networks) or continuous objects (probability or…

Classical Analysis and ODEs · Mathematics 2019-11-13 Alexander Belton , Dominique Guillot , Apoorva Khare , Mihai Putinar

In kernel methods, temporal information on the data is commonly included by using time-delayed embeddings as inputs. Recently, an alternative formulation was proposed by defining a gamma-filter explicitly in a reproducing kernel Hilbert…

Machine Learning · Statistics 2017-06-13 Steven Van Vaerenbergh , Simone Scardapane , Ignacio Santamaria

In this paper we consider the problems of supervised classification and regression in the case where attributes and labels are functions: a data is represented by a set of functions, and the label is also a function. We focus on the use of…

Machine Learning · Computer Science 2016-11-03 Hachem Kadri , Emmanuel Duflos , Philippe Preux , Stéphane Canu , Alain Rakotomamonjy , Julien Audiffren

We describe the structure of all bijective maps on the cone of positive definite operators acting on a finite and at least two-dimensional complex Hilbert space which preserve the quantum $\chi_\alpha^2$-divergence for some $\alpha \in…

Mathematical Physics · Physics 2018-02-16 Hong-Yi Chen , György Pál Gehér , Chih-Neng Liu , Lajos Molnár , Dániel Virosztek , Ngai-Ching Wong

We present a characterization for a positive definite operator valued kernel to be universal or $C_{0}$-universal, and apply these characterizations to a family of operator valued kernels that are shown to be well behaved. Later, we obtain…

Functional Analysis · Mathematics 2020-03-26 Jean Carlo Guella

We analyze in this paper a random feature map based on a theory of invariance I-theory introduced recently. More specifically, a group invariant signal signature is obtained through cumulative distributions of group transformed random…

Machine Learning · Computer Science 2015-12-07 Youssef Mroueh , Stephen Voinea , Tomaso Poggio

We study a reproducing kernel Hilbert space of functions defined on the positive integers and associated to the binomial coefficients. We introduce two transforms, which allow us to develop a related harmonic analysis in this Hilbert space.…

Complex Variables · Mathematics 2014-12-19 Daniel Alpay , Palle Jorgensen

We introduce the Yat kernel $$k_{b,\varepsilon}(\mathbf{w},\mathbf{x})=\frac{(\mathbf{w}^\top\mathbf{x}+b)^2}{\|\mathbf{x}-\mathbf{w}\|^2+\varepsilon},\qquad b\ge 0,\ \varepsilon>0,$$ a rational hidden-unit primitive whose units are Mercer…

Machine Learning · Computer Science 2026-05-06 Taha Bouhsine

The theory of positive maps plays a central role in operator algebras and functional analysis, and has countless applications in quantum information science. The theory was originally developed for operators acting on complex Hilbert…

Quantum Physics · Physics 2023-06-07 Giulio Chiribella , Kenneth R. Davidson , Vern I. Paulsen , Mizanur Rahaman

The unitary equivalence of $2$-isometric operators satisfying the so-called kernel condition is characterized. It relies on a model for such operators built on operator valued unilateral weighted shifts and on a characterization of the…

Functional Analysis · Mathematics 2018-06-11 Akash Anand , Sameer Chavan , Zenon Jan Jabłoński , Jan Stochel

Hilbertian kernel methods and their positive semidefinite kernels have been extensively used in various fields of applied mathematics and machine learning, owing to their several equivalent characterizations. We here unveil an analogy with…

Functional Analysis · Mathematics 2023-01-10 Pierre-Cyril Aubin-Frankowski , Stéphane Gaubert