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We give new proofs of asymptotic upper bounds of coding theory obtained within the frame of Delsarte's linear programming method. The proofs rely on the analysis of eigenvectors of some finite-dimensional operators related to orthogonal…

Information Theory · Computer Science 2019-05-14 Alexander Barg , Dmitry Nogin

In this note, we extend the result of \cite{PoulyG16} about the complexity of solving polynomial differential equations over unbounded domains to work with non-rational input. In order to deal with arbitrary input, we phrase the result in…

Computational Complexity · Computer Science 2016-08-02 Amaury Pouly

An efficient algorithm is developed that identifies all independencies implied by the topology of a Bayesian network. Its correctness and maximality stems from the soundness and completeness of d-separation with respect to probability…

Artificial Intelligence · Computer Science 2013-04-08 Dan Geiger , Tom S. Verma , Judea Pearl

Iterative numerical algorithms are typically equipped with a stopping criterion, where the iteration process is terminated when some error or misfit measure is deemed to be below a given tolerance. This is a useful setting for comparing…

Numerical Analysis · Computer Science 2014-12-04 Uri Ascher , Farbod Roosta-Khorasani

A characteristic feature of differential-algebraic equations is that one needs to find derivatives of some of their equations with respect to time, as part of so called index reduction or regularisation, to prepare them for numerical…

Numerical Analysis · Mathematics 2017-03-28 John D. Pryce , Nedialko S. Nedialkov , Guangning Tan , Xiao Li

Recent years have witnessed a growth in mathematics for deep learning--which seeks a deeper understanding of the concepts of deep learning with mathematics and explores how to make it more robust--and deep learning for mathematics, where…

Machine Learning · Computer Science 2023-10-31 Derick Nganyu Tanyu , Jianfeng Ning , Tom Freudenberg , Nick Heilenkötter , Andreas Rademacher , Uwe Iben , Peter Maass

We consider linear systems of recurrence equations whose coefficients are given in terms of indefinite nested sums and products covering, e.g., the harmonic numbers, hypergeometric products, $q$-hypergeometric products or their mixed…

Symbolic Computation · Computer Science 2017-05-02 Johannes Middeke , Carsten Schneider

We introduce efficient differentially private (DP) algorithms for several linear algebraic tasks, including solving linear equalities over arbitrary fields, linear inequalities over the reals, and computing affine spans and convex hulls. As…

Data Structures and Algorithms · Computer Science 2024-11-06 Haim Kaplan , Yishay Mansour , Shay Moran , Uri Stemmer , Nitzan Tur

We study sequential prediction of real-valued, arbitrary and unknown sequences under the squared error loss as well as the best parametric predictor out of a large, continuous class of predictors. Inspired by recent results from…

Machine Learning · Computer Science 2014-01-24 N. Denizcan Vanli , Suleyman S. Kozat

For a linear difference equation with the coefficients being computable sequences, we establish algorithmic undecidability of the problem of determining the dimension of the solution space including the case when some additional prior…

Symbolic Computation · Computer Science 2024-10-08 Sergei Abramov , Gleb Pogudin

In studying the complexity of iterative processes it is usually assumed that the arithmetic operations of addition, multiplication, and division can be performed in certain constant times. This assumption is invalid if the precision…

Computational Complexity · Computer Science 2021-03-22 Richard P. Brent

We propose a model for deterministic distributed function computation by a network of identical and anonymous nodes. In this model, each node has bounded computation and storage capabilities that do not grow with the network size.…

Optimization and Control · Mathematics 2011-06-28 Julien M. Hendrickx , Alex Olshevsky , John N. Tsitsiklis

This paper considers an optimization problem for a dynamical system whose evolution depends on a collection of binary decision variables. We develop scalable approximation algorithms with provable suboptimality bounds to provide…

Optimization and Control · Mathematics 2016-10-31 Insoon Yang , Samuel A. Burden , Ram Rajagopal , S. Shankar Sastry , Claire J. Tomlin

We study the zero sets of the independence polynomial on recursive sequences of graphs. We prove that for a maximally independent starting graph and a stable and expanding recursion algorithm, the zeros of the independence polynomial are…

Dynamical Systems · Mathematics 2024-11-25 Mikhail Hlushchanka , Han Peters

We generalize the differential dimension polynomial from prime differential ideals to characterizable differential ideals. Its computation is algorithmic, its degree and leading coefficient remain differential birational invariants, and it…

Commutative Algebra · Mathematics 2014-01-25 Markus Lange-Hegermann

Holomorphic functions are amazing because their values in an ever so small disk in the complex plane completely determine the function values at arbitrary points in their maximum possible domain. The process of extending such a function…

Complex Variables · Mathematics 2015-05-15 Stefan Kranich

We present a prototypical linear algebra compiler that automatically exploits domain-specific knowledge to generate high-performance algorithms. The input to the compiler is a target equation together with knowledge of both the structure of…

Mathematical Software · Computer Science 2012-05-29 Diego Fabregat-Traver , Paolo Bientinesi

We compute the graded polynomial identities of the infinite dimensional upper triangular matrix algebra over an arbitrary field. If the grading group is finite, we prove that the set of graded polynomial identities admits a finite basis. We…

Rings and Algebras · Mathematics 2024-02-19 Micael Said Garcia , Felipe Yukihide Yasumura

We consider the uniqueness of solutions of ordinary differential equations where the coefficients may have singularities. We derive upper bounds on the the order of singularities of the coefficients and provide examples to illustrate the…

Classical Analysis and ODEs · Mathematics 2008-12-19 Yifei Pan , Mei Wang

Recent work on Path-Dependent Partial Differential Equations (PPDEs) has shown that PPDE solutions can be approximated by a probabilistic representation, implemented in the literature by the estimation of conditional expectations using…

Machine Learning · Computer Science 2022-10-05 Jiang Yu Nguwi , Nicolas Privault
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