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Related papers: Optimal systems of fundamental S-units for LLL-red…

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In this paper we improve upon in terms of S the best known effective upper bounds for the solutions of S-unit equations and decomposable form equations.

Number Theory · Mathematics 2019-02-01 Kálmán Győry

We give improved lower bounds for the number of solutions of some $S$-unit equations over the integers, by counting the solutions of some associated linear equations as the coefficients in those equations vary over sparse sets. This method…

Number Theory · Mathematics 2011-08-19 Adam J. Harper

We present a complexity reduction algorithm for a family of parameter-dependent linear systems when the system parameters belong to a compact semi-algebraic set. This algorithm potentially describes the underlying dynamical system with…

Systems and Control · Computer Science 2012-09-25 Farhad Farokhi , Henrik Sandberg , Karl H. Johansson

Statistical Linkage Learning (SLL) is a part of many state-of-the-art optimizers. The purpose of SLL is to discover variable interdependencies. It has been shown that the effectiveness of SLL-using optimizers is highly dependent on the…

Neural and Evolutionary Computing · Computer Science 2025-03-25 Michal Prusik , Bartosz Frej , Michal W. Przewozniczek

We obtain upper bounds on the number of finite sets $\mathcal S$ of primes below a given bound for which various $2$ variable $\mathcal S$-unit equations have a solution.

Number Theory · Mathematics 2020-07-31 I. E. Shparlinski , C. L. Stewart

Structural resolution (or S-resolution) is a newly proposed alternative to SLD-resolution that allows a systematic separation of derivations into term-matching and unification steps. Productive logic programs are those for which…

Logic in Computer Science · Computer Science 2015-06-23 Peng Fu , Ekaterina Komendantskaya

We present algorithms for efficiently learning regularizers that improve generalization. Our approach is based on the insight that regularizers can be viewed as upper bounds on the generalization gap, and that reducing the slack in the…

Machine Learning · Computer Science 2019-02-25 Matthew Streeter

Modeling of physical systems includes extensive use of software packages that implement the accurate finite element method for solving differential equations considered along with the appropriate initial and boundary conditions. When the…

Computational Engineering, Finance, and Science · Computer Science 2018-03-20 O. Kononenko , I. Kononenko

Asking for the optimal protocol of an external control parameter that minimizes the mean work required to drive a nano-scale system from one equilibrium state to another in finite time, Schmiedl and Seifert ({\it Phys. Rev. Lett.} {\bf 98},…

Statistical Mechanics · Physics 2008-04-14 Holger Then , Andreas Engel

We study orbit-finite systems of linear equations, in the setting of sets with atoms. Our principal contribution is a decision procedure for solvability of such systems. The procedure works for every field (and even commutative ring) under…

Computation and Language · Computer Science 2024-02-28 Arka Ghosh , Piotr Hofman , Sławomir Lasota

We derive and investigate lower bounds for the potential energy of finite spherical point sets (spherical codes). Our bounds are optimal in the following sense -- they cannot be improved by employing polynomials of the same or lower degrees…

Metric Geometry · Mathematics 2015-03-26 P. G. Boyvalenkov , P. D. Dragnev , D. P. Hardin , E. B. Saff , M. M. Stoyanova

We consider Continuous Linear Programs over a continuous finite time horizon $T$, with linear cost coefficient functions, linear right hand side functions, and a constant coefficient matrix, as well as their symmetric dual. We search for…

Optimization and Control · Mathematics 2014-12-02 Evgeny Shindin , Gideon Weiss

This paper introduces a novel Large Language Models (LLMs)-assisted agent that automatically converts natural-language descriptions of power system optimization scenarios into compact, solver-ready formulations and generates corresponding…

Artificial Intelligence · Computer Science 2025-08-12 Yunkai Hu , Tianqiao Zhao , Meng Yue

This paper considers the hyperparameter optimization problem of mathematical techniques that arise in the numerical solution of differential and integral equations. The well-known approaches grid and random search, in a parallel algorithm…

Numerical Analysis · Mathematics 2023-04-28 Alireza Afzal Aghaei , Kourosh Parand

A Line Replaceable Unit (LRU) is a collection of connected parts in a system that is replaced when any part of the LRU fails. Companies use LRUs as a mechanism to reduce downtime of systems following a failure. The design of LRUs determines…

Optimization and Control · Mathematics 2023-08-08 Joni Driessen , Joost de Kruijf , Joachim Arts , Geert-Jan van Houtum

We consider the problem of robust matrix completion, which aims to recover a low rank matrix $L_*$ and a sparse matrix $S_*$ from incomplete observations of their sum $M=L_*+S_*\in\mathbb{R}^{m\times n}$. Algorithmically, the robust matrix…

Machine Learning · Statistics 2020-03-25 Yunfeng Cai , Ping Li

To solve unmodeled optimization problems with hard constraints, this paper proposes a novel zeroth-order approach called Safe Zeroth-order Optimization using Linear Programs (SZO-LP). The SZO-LP method solves a linear program in each…

Optimization and Control · Mathematics 2023-04-05 Baiwei Guo , Yang Wang , Yuning Jiang , Maryam Kamgarpour , Giancarlo Ferrari-Trecate

Linear equations play a pivotal role in many areas of science and engineering, making efficient solutions to linear systems highly desirable. The development of quantum algorithms for solving linear systems has been a significant…

Quantum Physics · Physics 2025-02-20 Nhat A. Nghiem

Let $T$ be a positive integer, and $\mathcal{M}$ be a finitely presented module over the Laurent polynomial ring $\mathbb{Z}_{/T}[X_1^{\pm}, \ldots, X_N^{\pm}]$. We consider S-unit equations over $\mathcal{M}$: these are equations of the…

Number Theory · Mathematics 2025-05-28 Ruiwen Dong , Doron Shafrir

This paper presents a new exact method to calculate worst-case parameter realizations in two-stage robust optimization problems with categorical or binary-valued uncertain data. Traditional exact algorithms for these problems, notably…

Optimization and Control · Mathematics 2022-01-19 Anirudh Subramanyam
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