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To reversify an arbitrary sequential algorithm $A$, we gently instrument $A$ with bookkeeping machinery. The result is a step-for-step reversible algorithm that mimics $A$ step-for-step and stops exactly when $A$ does. Without loss of…

Quantum Physics · Physics 2021-06-29 Yuri Gurevich

Given a polynomial system f associated with a simple multiple zero x of multiplicity {\mu}, we give a computable lower bound on the minimal distance between the simple multiple zero x and other zeros of f. If x is only given with limited…

Numerical Analysis · Mathematics 2017-03-14 Zhiwei Hao , Wenrong Jiang , Nan Li , Lihong Zhi

The program Reverse Mathematics in the foundations of mathematics seeks to identify the minimal axioms required to prove theorems of ordinary mathematics. One always assumes the base theory, a logical system embodying computable…

Logic · Mathematics 2024-06-18 Dag Normann , Sam Sanders

We consider a setting where a verifier with limited computation power delegates a resource intensive computation task---which requires a $T\times S$ computation tableau---to two provers where the provers are rational in that each prover…

Computer Science and Game Theory · Computer Science 2022-06-15 Yuqing Kong , Chris Peikert , Grant Schoenebeck , Biaoshuai Tao

We describe several technical tools that prove to be efficient for investigating the rewrite systems associated with a family of algebraic laws, and might be useful for more general rewrite systems. These tools consist in introducing a…

Logic in Computer Science · Computer Science 2007-05-23 Patrick Dehornoy

We develop quaternion--native iterative methods for computing the Moore--Penrose (MP) pseudoinverse of quaternion matrices and analyze their convergence. Our starting point is a damped Newton--Schulz (NS) iteration tailored to…

Numerical Analysis · Mathematics 2025-10-10 Valentin Leplat , Salman Ahmadi-Asl , JunJun Pan , Ning Zheng

Inverse optimization describes a process that is the "reverse" of traditional mathematical optimization. Unlike traditional optimization, which seeks to compute optimal decisions given an objective and constraints, inverse optimization…

Optimization and Control · Mathematics 2022-07-28 Timothy C. Y. Chan , Rafid Mahmood , Ian Yihang Zhu

In various areas of computer science, we deal with a set of constraints to be satisfied. If the constraints cannot be satisfied simultaneously, it is desirable to identify the core problems among them. Such cores are called minimal…

Logic in Computer Science · Computer Science 2018-05-09 Jaroslav Bendik , Ivana Cerna , Nikola Benes

Recursive estimates of large systems of equations in the context of least squares fitting is a common practice in different fields of study. For example, recursive adaptive filtering is extensively used in signal processing and control…

Numerical Analysis · Mathematics 2018-01-04 Nasser Kazemi , Mauricio Sacchi

In the first part of this paper we give an elementary proof of the fact that if an infinite matrix $A$, which is invertible as a bounded operator on $\ell^2$, can be uniformly approximated by banded matrices then so can the inverse of $A$.…

Statistics Theory · Mathematics 2010-02-25 Peter J. Bickel , Marko Lindner

We study the Reverse algorithm, a multidimensional continued fraction algorithm, which is not unimodular. We show that the Reverse algorithm is ergodic and, by proving that its second Lyapunov exponent is negative, that it is a.e.…

Dynamical Systems · Mathematics 2026-02-17 Hiroaki Ito , Niels Langeveld , Jörg Thuswaldner

We present an algorithm for finding all time-reversible systems within a given family of 2-dim systems of ODE's whose right-hand sides are polynomials. We also study an interconnection of time-reversibility and invariants of a subgroup of…

Dynamical Systems · Mathematics 2007-05-23 Valery G. Romanovski

In computational design and fabrication, neural networks are becoming important surrogates for bulky forward simulations. A long-standing, intertwined question is that of inverse design: how to compute a design that satisfies a desired…

Graphics · Computer Science 2022-08-30 Navid Ansari , Hans-Peter Seidel , Vahid Babaei

A composite likelihood is a non-genuine likelihood function that allows to make inference on limited aspects of a model, such as marginal or conditional distributions. Composite likelihoods are not proper likelihoods and need therefore…

Methodology · Statistics 2021-04-06 Michele Lambardi di San Miniato , Nicola Sartori

We study the "top-to-random-and-reverse shuffle", defined as the top-to-random shuffle in the symmetric group algebra composed with the permutation $w_0$ (which sends each $i$ to $n+1-i$). More generally, we analyze the composition of any…

Combinatorics · Mathematics 2025-08-12 Darij Grinberg , Jonathan Parlett

Mixture models have received considerable attention recently and Newton [Sankhy\={a} Ser. A 64 (2002) 306--322] proposed a fast recursive algorithm for estimating a mixing distribution. We prove almost sure consistency of this recursive…

Statistics Theory · Mathematics 2009-08-25 Surya T. Tokdar , Ryan Martin , Jayanta K. Ghosh

Sine-skewed circular distributions are identifiable and have easily-computable trigonometric moments and a simple random number generation algorithm, whereas they are known to have relatively low levels of asymmetry. This study proposes a…

Methodology · Statistics 2024-02-16 Yoichi Miyata , Takayuki Shiohama , Toshihiro Abe

In this text I present a couple of new principles and thereon based iterative methods for numerical solution of sequences of systems of linear equations with fixed system matrix and changing right-hand-sides. The use of the new methods is…

Numerical Analysis · Mathematics 2015-12-17 Martin Neuenhofen

Every function over the natural numbers has an infinite subdomain on which the function is non-decreasing. Motivated by a question of Dzhafarov and Schweber, we study the reverse mathematics of variants of this statement. It turns out that…

Logic · Mathematics 2016-03-30 Ludovic Patey

Many neural learning algorithms require to solve large least square systems in order to obtain synaptic weights. Moore-Penrose inverse matrices allow for solving such systems, even with rank deficiency, and they provide minimum-norm vectors…

Neural and Evolutionary Computing · Computer Science 2008-12-18 Pierre Courrieu
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