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Interior-point methods for linear programming problems require the repeated solution of a linear system of equations. Solving these linear systems is non-trivial due to the severe ill-conditioning of the matrices towards convergence. This…

Optimization and Control · Mathematics 2021-05-05 Jeffrey Cornelis , Wim Vanroose

We present a method for verifying partial correctness properties of imperative programs that manipulate integers and arrays by using techniques based on the transformation of constraint logic programs (CLP). We use CLP as a metalanguage for…

Programming Languages · Computer Science 2013-09-23 Emanuele De Angelis , Fabio Fioravanti , Alberto Pettorossi , Maurizio Proietti

In this paper we present an efficient algorithm for bivariate interpolation, which is based on the use of the partition of unity method for constructing a global interpolant. It is obtained by combining local radial basis function…

Numerical Analysis · Mathematics 2014-08-04 Roberto Cavoretto

The main computational steps in algebraic soft-decoding, as well as Sudan-type list-decoding, of Reed-Solomon codes are bivariate polynomial interpolation and factorization. We introduce a computational technique, based upon re-encoding and…

Information Theory · Computer Science 2015-03-17 Ralf Koetter , Jun Ma , Alexander Vardy

Multipoint secant and interpolation methods are effective tools for solving systems of nonlinear equations. They use quasi-Newton updates for approximating the Jacobian matrix. Owing to their ability to more completely utilize the…

Optimization and Control · Mathematics 2017-12-05 Oleg Burdakov , Ahmad Kamandi

We present the real interpolation with variable exponent and we prove the basic properties in analogy to the classical real interpolation. More precisely, we prove that under some additional conditions, this method can be reduced to the…

Functional Analysis · Mathematics 2017-03-16 Douadi Drihem

Spline interpolation has been used in several applications due to its favorable properties regarding smoothness and accuracy of the interpolant. However, when there exists a discontinuity or a steep gradient in the data, some artifacts can…

Numerical Analysis · Mathematics 2021-12-21 Francesc Aràndiga , Antonio Baeza , Dionisio F. Yáñez

Matrices resulting from the discretization of a kernel function, e.g., in the context of integral equations or sampling probability distributions, can frequently be approximated by interpolation. In order to improve the efficiency, a…

Numerical Analysis · Mathematics 2021-12-10 Steffen Börm

In this paper, applied strictly monotonic increasing scaled maps, a kind of well-conditioned linear barycentric rational interpolations are proposed to approximate functions of singularities at the origin, such as $x^\alpha$ for $\alpha \in…

Numerical Analysis · Mathematics 2021-01-21 Desong Kong , Shuhuang Xiang

The relationship between interpolation and separation properties of hypersurfaces in Bargmann-Fock spaces over $\mathbb{C} ^n$ is not well-understood except for $n=1$. We present four examples of smooth affine algebraic hypersurfaces that…

Complex Variables · Mathematics 2018-10-03 Vamsi Pingali , Dror Varolin

We present a formal tool for verification of multivariate nonlinear inequalities. Our verification method is based on interval arithmetic with Taylor approximations. Our tool is implemented in the HOL Light proof assistant and it is capable…

Logic in Computer Science · Computer Science 2013-05-22 Alexey Solovyev , Thomas C. Hales

Answer Set Programming (ASP) is an important logic programming paradigm within the field of Knowledge Representation and Reasoning. As a concise, human-readable, declarative language, ASP is an excellent tool for developing trustworthy…

Logic in Computer Science · Computer Science 2025-02-14 Zachary Hansen

We investigate an interpolation/extrapolation method that, given scattered observations of the Fourier transform, approximates its inverse. The interpolation algorithm takes advantage of modelling the available data via a shape-driven…

Numerical Analysis · Mathematics 2021-09-22 Emma Perracchione , Anna Maria Massone , Michele Piana

The polynomial kernels are widely used in machine learning and they are one of the default choices to develop kernel-based classification and regression models. However, they are rarely used and considered in numerical analysis due to their…

We study the problem of verifiable polynomial evaluation in the user-server and multi-party setups. We propose {INTERPOL}, an information-theoretically verifiable algorithm that allows a user to delegate the evaluation of a polynomial to a…

Cryptography and Security · Computer Science 2019-04-30 Saeid Sahraei , A. Salman Avestimehr

In order to verify programs or hybrid systems, one often needs to prove that certain formulas are unsatisfiable. In this paper, we consider conjunctions of polynomial inequalities over the reals. Classical algorithms for deciding these not…

Numerical Analysis · Mathematics 2009-02-02 David Monniaux

For regularized optimization that minimizes the sum of a smooth term and a regularizer that promotes structured solutions, inexact proximal-Newton-type methods, or successive quadratic approximation (SQA) methods, are widely used for their…

Optimization and Control · Mathematics 2023-05-02 Ching-pei Lee

Although 3D shape matching and interpolation are highly interrelated, they are often studied separately and applied sequentially to relate different 3D shapes, thus resulting in sub-optimal performance. In this work we present a unified…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Dongliang Cao , Marvin Eisenberger , Nafie El Amrani , Daniel Cremers , Florian Bernard

Existing structural analysis methods may fail to find all hidden constraints for a system of differential-algebraic equations with parameters if the system is structurally unamenable for certain values of the parameters. In this paper, for…

Numerical Analysis · Mathematics 2024-01-11 Wenqiang Yang , Wenyuan Wu , Greg Reid

In this paper we explore acceleration techniques for large scale nonconvex optimization problems with special focuses on deep neural networks. The extrapolation scheme is a classical approach for accelerating stochastic gradient descent for…

Machine Learning · Statistics 2018-05-18 Guangzeng Xie , Yitan Wang , Shuchang Zhou , Zhihua Zhang