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The Empirical Interpolation Method (EIM) is a greedy procedure that constructs approximate representations of two-variable functions in separated form. In its classical presentation, the two variables play a non-symmetric role. In this…

Numerical Analysis · Mathematics 2019-08-12 Fabien Casenave , Alexandre Ern , Tony Lelièvre

We present a novel method to significantly speed up cosmological parameter sampling. The method relies on constructing an interpolation of the CMB-log-likelihood based on sparse grids, which is used as a shortcut for the…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-18 Mona Frommert , Dirk Pflueger , Thomas Riller , Martin Reinecke , Hans-Joachim Bungartz , Torsten Ensslin

Interpolation is responsible for digital signal resampling and can significantly degrade the original signal quality if not done properly. For many years, optimal interpolation algorithms were sought within constrained classes of…

Computer Vision and Pattern Recognition · Computer Science 2011-04-23 Oleg S. Pianykh

Numerical integrations in celestial mechanics often involve the repeated computation of a rotation with a constant angle. A direct evaluation of these rotations yields a linear drift of the distance to the origin. This is due to roundoff in…

Numerical Analysis · Mathematics 2025-10-20 M. Henon , J-M. Petit

Unlike matrix completion, tensor completion does not have an algorithm that is known to achieve the information-theoretic sample complexity rate. This paper develops a new algorithm for the special case of completion for nonnegative…

Machine Learning · Computer Science 2022-05-25 Caleb Bugg , Chen Chen , Anil Aswani

This paper studies path synthesis for nonholonomic mobile robots moving in two-dimensional space. We first address the problem of interpolating paths expressed as sequences of straight line segments, such as those produced by some planning…

Robotics · Computer Science 2015-08-12 Stéphane Lens , Bernard Boigelot

Based on the sampling theorem, interpolation should be conducted by employing the sinc functions as the kernels. Inspired by the fact that the discrete Fourier transform (DFT) is sampled from the discrete time Fourier transform, a fast…

Signal Processing · Electrical Eng. & Systems 2024-07-10 Zijun Gong

We pose the deterministic, nonparametric, approximation problem for scalar nonnegative input/output systems via finite impulse response convolutions, based on repeated observations of input/output signal pairs. The problem is converted into…

Optimization and Control · Mathematics 2015-07-14 Lorenzo Finesso , Peter Spreij

A convergent algorithm for nonnegative matrix factorization with orthogonality constraints imposed on both factors is proposed in this paper. This factorization concept was first introduced by Ding et al. with intent to further improve…

Machine Learning · Computer Science 2018-11-16 Andri Mirzal

We introduce novel mathematical and computational tools to develop a complete algorithm for computing the set of non-properness of polynomials maps in the plane. In particular, this set, which we call \emph{the Jelonek set}, is a subset of…

Algebraic Geometry · Mathematics 2023-06-27 Boulos El Hilany , Elias Tsigaridas

In this paper we provide the exact asymptotics of the optimal weighted $L_p$-error, $0<p< \infty$, of linear spline interpolation of $C^2$ functions with positive Hessian. The full description of the behavior of the optimal error leads to…

Numerical Analysis · Mathematics 2015-03-17 Vladislav Babenko , Yuliya Babenko , Dmytro Skorokhodov

A symmetric nonnegative matrix factorization algorithm based on self-paced learning was proposed to improve the clustering performance of the model. It could make the model better distinguish normal samples from abnormal samples in an…

Machine Learning · Computer Science 2024-10-22 Lei Wang , Liang Du , Peng Zhou , Peng Wu

In this paper, we introduce the neural empirical interpolation method (NEIM), a neural network-based alternative to the discrete empirical interpolation method for reducing the time complexity of computing the nonlinear term in a reduced…

Numerical Analysis · Mathematics 2025-05-13 Max Hirsch , Federico Pichi , Jan S. Hesthaven

Image interpolation is a special case of image super-resolution, where the low-resolution image is directly down-sampled from its high-resolution counterpart without blurring and noise. Therefore, assumptions adopted in super-resolution…

Image and Video Processing · Electrical Eng. & Systems 2020-10-28 Junchao Zhang

In this paper we propose a fast algorithm for trivariate interpolation, which is based on the partition of unity method for constructing a global interpolant by blending local radial basis function interpolants and using locally supported…

Numerical Analysis · Mathematics 2015-10-20 Roberto Cavoretto , Alessandra De Rossi

Nonlinear dimensionality reduction embeddings computed from datasets do not provide a mechanism to compute the inverse map. In this paper, we address the problem of computing a stable inverse map to such a general bi-Lipschitz map. Our…

Numerical Analysis · Mathematics 2013-11-06 Nathan D. Monnig , Bengt Fornberg , Francois G. Meyer

Finding an exact maximum distance of two points in the given set is a fundamental computational problem which is solved in many applications. This paper presents a fast, simple to implement and robust algorithm for finding this maximum…

Data Structures and Algorithms · Computer Science 2017-08-10 Vaclav Skala , Zuzana Majdisova

We present an algorithm for constructing the fixed point of a general non-isometric similarity of the plane.

History and Overview · Mathematics 2014-11-03 Zhigang Han , Ron Umble

The nonnegative matrix factorization is a widely used, flexible matrix decomposition, finding applications in biology, image and signal processing and information retrieval, among other areas. Here we present a related matrix factorization.…

Machine Learning · Statistics 2017-12-12 David W Dreisigmeyer

Simply put, a sparse polynomial is one whose zero coefficients are not explicitly stored. Such objects are ubiquitous in exact computing, and so naturally we would like to have efficient algorithms to handle them. However, with this compact…

Symbolic Computation · Computer Science 2018-07-24 Daniel S. Roche
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