English
Related papers

Related papers: Positive definiteness of real quadratic forms resu…

200 papers

We study kernel quadrature rules with convex weights. Our approach combines the spectral properties of the kernel with recombination results about point measures. This results in effective algorithms that construct convex quadrature rules…

Numerical Analysis · Mathematics 2022-10-12 Satoshi Hayakawa , Harald Oberhauser , Terry Lyons

Finite element approximation to a decoupled formulation for the quad--curl problem is studied in this paper. The difficulty of constructing elements with certain conformity to the quad--curl problems has been greatly reduced. For convex…

Numerical Analysis · Mathematics 2021-12-09 Shuhao Cao , Long Chen , Xuehai Huang

We consider the problem of discretizing evolution operators of linear delay equations with the aim of approximating their spectra, which is useful in investigating the stability properties of (nonlinear) equations via the principle of…

Numerical Analysis · Mathematics 2026-01-01 Alessia andò , Giusy Bosco , Dimitri Breda , Davide Liessi

The robust distributed state estimation for a class of continuous-time linear time-invariant systems is achieved by a novel kernel-based distributed observer, which, for the first time, ensures fixed-time convergence properties. The…

Systems and Control · Electrical Eng. & Systems 2022-09-21 Pudong Ge , Peng Li , Boli Chen , Fei Teng

Identifying coherent spatiotemporal patterns generated by complex dynamical systems is a central problem in many science and engineering disciplines. Here, we combine ideas from the theory of operator-valued kernels with delay-embedding…

Data Analysis, Statistics and Probability · Physics 2018-05-24 Dimitrios Giannakis , Joanna Slawinska , Abbas Ourmazd , Zhizhen Zhao

Determinantal point processes (DPPs) offer an elegant tool for encoding probabilities over subsets of a ground set. Discrete DPPs are parametrized by a positive semidefinite matrix (called the DPP kernel), and estimating this kernel is key…

Machine Learning · Computer Science 2015-10-12 Zelda Mariet , Suvrit Sra

In this paper, we further develop the approach, originating in [14 (arXiv:1311.6765),20 (arXiv:1604.02576)], to "computation-friendly" hypothesis testing and statistical estimation via Convex Programming. Specifically, we focus on…

Statistics Theory · Mathematics 2018-04-16 Anatoli Juditsky , Arkadi Nemirovski

The two-step backward differential formula (BDF2) with unequal time-steps is applied to construct an energy stable convex-splitting scheme for the Cahn-Hilliard model. We focus on the numerical influences of time-step variations by using…

Numerical Analysis · Mathematics 2023-01-31 Hong-lin Liao , Bingquan Ji , Lin Wang , Zhimin Zhang

Standard convolutions are prevalent in image processing and deep learning, but their fixed kernels limits adaptability. Several deformation strategies of the reference kernel grid have been proposed. Yet, they lack a unified theoretical…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Thomas Dagès , Michael Lindenbaum , Alfred M. Bruckstein

The nonlocal Cahn-Hilliard equation provides a natural extension of the classical model for phase separation by incorporating long-range interactions through a singular convolution kernel. While this formulation admits a rich existence and…

Numerical Analysis · Mathematics 2026-04-22 Andrés Miniguano-Trujillo , Andrea Poiatti , Maurizio Grasselli , Benjamin Goddard , John Pearson

This paper concerns the tilt stability of local optimal solutions to a class of nonlinear semidefinite programs, which involves a twice continuously differentiable objective function and a convex feasible set. By leveraging the second…

Optimization and Control · Mathematics 2024-12-24 Yulan Liu , Shaohua Pan , Shujun Bi

We prove new characterisations of exponential stability for positive linear discrete-time systems in ordered Banach spaces, in terms of small-gain conditions. Such conditions have played an important role in the finite-dimensional systems…

Functional Analysis · Mathematics 2021-07-19 Jochen Glück , Andrii Mironchenko

The paper introduces a new characterisation of strictly positive definiteness for kernels on the 2-sphere without assuming the kernel to be radially (isotropic) or axially symmetric. The results use the series expansion of the kernel in…

Numerical Analysis · Mathematics 2022-05-06 Janin Jäger

The accurate representation of epistemic uncertainty is a challenging yet essential task in machine learning. A widely used representation corresponds to convex sets of probabilistic predictors, also known as credal sets. One popular way of…

Machine Learning · Computer Science 2025-07-30 Mira Jürgens , Thomas Mortier , Eyke Hüllermeier , Viktor Bengs , Willem Waegeman

In the vicinity of a solution of a nonlinear programming problem at which both strict complementarity and linear independence of the active constraints may fail to hold, we describe a technique for distinguishing weakly active from strongly…

Optimization and Control · Mathematics 2025-10-20 Stephen J. Wright

We present an alternative way of solving the steerable kernel constraint that appears in the design of steerable equivariant convolutional neural networks. We find explicit real and complex bases which are ready to use, for different…

Machine Learning · Computer Science 2026-03-16 Alan Garbarz

We establish that stabilization of a class of linear, hyperbolic partial differential equations (PDEs) with a large (nevertheless finite) number of components, can be achieved via employment of a backstepping-based control law, which is…

Optimization and Control · Mathematics 2024-11-05 Jukka-Pekka Humaloja , Nikolaos Bekiaris-Liberis

We consider the approximation of weakly T-coercive operators. The main property to ensure the convergence thereof is the regularity of the approximation (in the vocabulary of discrete approximation schemes). In a previous work the existence…

Numerical Analysis · Mathematics 2025-04-17 Martin Halla , Christoph Lehrenfeld , Paul Stocker

For the real, continuous, isotropic and positive definite kernels on a product of spheres, one may consider not only its usual strict positive definiteness but also strict positive definiteness restrict to the points of the product that…

Classical Analysis and ODEs · Mathematics 2015-05-15 Jean C. Guella , Valdir A. Menegatto

This paper presents a convergence analysis of kernel-based quadrature rules in misspecified settings, focusing on deterministic quadrature in Sobolev spaces. In particular, we deal with misspecified settings where a test integrand is less…

Numerical Analysis · Mathematics 2018-10-31 Motonobu Kanagawa , Bharath K. Sriperumbudur , Kenji Fukumizu