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Regular model checking is a well-established technique for the verification of regular transition systems (RTS): transition systems whose initial configurations and transition relation can be effectively encoded as regular languages. In…

Formal Languages and Automata Theory · Computer Science 2025-06-24 Javier Esparza , Valentin Krasotin

We use convex relaxation techniques to provide a sequence of solutions to the matrix completion problem. Using the nuclear norm as a regularizer, we provide simple and very efficient algorithms for minimizing the reconstruction error…

Machine Learning · Statistics 2009-06-12 Rahul Mazumder , Trevor Hastie , Rob Tibshirani

The purpose of this work is to produce a regularity theory for a class of parabolic Isaacs equations. Our techniques are based on approximation methods which allow us to connect our problem with a Bellman parabolic model. An approximation…

Analysis of PDEs · Mathematics 2022-01-13 Pêdra D. S. Andrade , Giane C. Rampasso , Makson S. Santos

Based on differences of points and differences of gradients over the most recent three iterations, together with the Taylor's theorem, two forms of the quasi-Newton equations at the recent iteration are constructed. By using the two forms…

Optimization and Control · Mathematics 2022-06-15 Sun Qingying , Zhao Xu , Wang Jian

Novel sequences of approximants to solutions of Painlev\'e II on finite intervals of the real line, with Neumann boundary conditions, are constructed. Numerical experiments strongly suggest convergence of these sequences in a surprisingly…

Mathematical Physics · Physics 2020-07-13 A. J. Bracken

A new method, called the method of self-similar approximants, and its recent developments are described. The method is based on the ideas of renormalization group theory and optimal control theory. It allows for the effective extrapolation…

Mathematical Physics · Physics 2025-05-20 V. I. Yukalov , E. P. Yukalova

This paper introduces a notion of regularity (or irregularity) of the point at infinity for the unbounded open subset of $\rr^{N}$ concerning second order uniformly elliptic equations with bounded and measurable coefficients, according as…

Analysis of PDEs · Mathematics 2015-06-09 Ugur G. Abdulla

Tikhonov regularization involves minimizing the combination of a data discrepancy term and a regularizing term, and is the standard approach for solving inverse problems. The use of non-convex regularizers, such as those defined by trained…

Optimization and Control · Mathematics 2023-02-20 Daniel Obmann , Markus Haltmeier

Several N-body problems in ordinary (3-dimensional) space are introduced which are characterized by Newtonian equations of motion (``acceleration equal force;'' in most cases, the forces are velocity-dependent) and are amenable to exact…

Mathematical Physics · Physics 2015-06-26 Massimo Bruschi , Francesco Calogero

In this paper we the formulation of inverse problems as constrained minimization problems and their iterative solution by gradient or Newton type. We carry out a convergence analysis in the sense of regularization methods and discuss…

Numerical Analysis · Mathematics 2021-01-15 Barbara Kaltenbacher , Kha Van Huynh

Universal spacetimes are spacetimes for which all conserved symmetric rank-2 tensors, constructed as contractions of polynomials from the metric, the Riemann tensor and its covariant derivatives of arbitrary order, are multiples of the…

General Relativity and Quantum Cosmology · Physics 2014-10-17 Sigbjørn Hervik , Vojtech Pravda , Alena Pravdova

Considering the three-dimensional incompressible Navier-Stokes equations on the whole space, we address the question: is it possible to infer global regularity of a mild solution from a single approximate solution? Assuming a relatively…

Analysis of PDEs · Mathematics 2021-09-02 Tuan N. Pham

In this work, we develop a new complexity metric for an important class of low-rank matrix optimization problems in both symmetric and asymmetric cases, where the metric aims to quantify the complexity of the nonconvex optimization…

Optimization and Control · Mathematics 2023-07-24 Haixiang Zhang , Baturalp Yalcin , Javad Lavaei , Somayeh Sojoudi

The development of energy selective, photon counting X-ray detectors allows for a wide range of new possibilities in the area of computed tomographic image formation. Under the assumption of perfect energy resolution, here we propose a…

Computer Vision and Pattern Recognition · Computer Science 2015-06-16 Oguz Semerci , Ning Hao , Misha E. Kilmer , Eric L. Miller

We revisit the regularity theory of Escauriaza, Seregin, and \v{S}ver\'ak for solutions to the three-dimensional Navier-Stokes equations which are uniformly bounded in the critical $L^3_x(\mathbf{R}^3)$ norm. By replacing all invocations of…

Analysis of PDEs · Mathematics 2020-07-13 Terence Tao

In this paper, we propose a third-order Newton's method which in each iteration solves a semidefinite program as a subproblem. Our approach is based on moving to the local minimum of the third-order Taylor expansion at each iteration,…

Optimization and Control · Mathematics 2023-06-08 Olha Silina , Jeffrey Zhang

We find the most general algebraic type N solution with non-vanishing scalar curvature, which comprises all type N solutions of new massive gravity in three dimensions. We also give the special forms of this solution, which correspond to…

High Energy Physics - Theory · Physics 2014-11-21 Haji Ahmedov , Alikram N. Aliev

This work investigates a new approach to find closed form analytical approximate solution of linear initial value problems. Classical Bernoulli polynomials have been used to derive a finite set of orthonormal polynomials and a finite…

Numerical Analysis · Mathematics 2020-07-27 Udaya Pratap Singh

In this paper, we propose new linearly convergent second-order methods for minimizing convex quartic polynomials. This framework is applied for designing optimization schemes, which can solve general convex problems satisfying a new…

Optimization and Control · Mathematics 2022-01-14 Yurii Nesterov

In this article we study the problem of recovering the unknown solution of a linear ill-posed problem, via iterative regularization methods. We review the problem of projection-regularization from a statistical point of view. A basic…

Statistics Theory · Mathematics 2007-06-13 Ana K. Fermin , Carenne Ludena