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We propose an algorithm to approximate solutions of global optimization problems in Sobolev spaces that follows the spirit of Consensus-based algorithms in finite dimensions. The main ingredient are Gaussian processes. In fact, we exploit…

Optimization and Control · Mathematics 2026-03-17 Mahmoud Khatab , Claudia Totzeck

A variety of logical frameworks support the use of higher-order abstract syntax in representing formal systems; however, each system has its own set of benchmarks. Even worse, general proof assistants that provide special libraries for…

Logic in Computer Science · Computer Science 2015-07-30 Amy Felty , Alberto Momigliano , Brigitte Pientka

Gaussian Boson Sampling (GBS) is capable of solving certain classes of graph problems owing to the samples produced by such a device having a connection to the hafnian matrix function. In particular, a GBS device has been shown to provide…

Quantum Physics · Physics 2026-05-28 Ewan Mer , Zhenghao Li , Shang Yu , Ian A. Walmsley , Raj B. Patel

Geometry processing presents a variety of difficult numerical problems, each seeming to require its own tailored solution. This breadth is largely due to the expansive list of geometric primitives, e.g., splines, triangles, and hexahedra,…

Computational Geometry · Computer Science 2021-10-19 Zoë Marschner , Paul Zhang , David Palmer , Justin Solomon

Semantics-Guided Synthesis (SemGuS) is a programmable framework for defining synthesis problems in a domain- and solver-agnostic way. This paper presents the standardized SemGuS format, together with an open-source toolkit that provides a…

Programming Languages · Computer Science 2024-06-05 Keith J. C. Johnson , Andrew Reynolds , Thomas Reps , Loris D'Antoni

Smoothness of generalized solutions for higher-order elliptic equations with nonlocal boundary conditions is studied in plane domains. Necessary and sufficient conditions upon the right-hand side of the problem and nonlocal operators under…

Analysis of PDEs · Mathematics 2014-06-25 Pavel Gurevich

In this paper, we develop a new concept of Global Curvature Bound for an arbitrary nonlinear operator between abstract metric spaces. We use this notion to characterize the global complexity of high-order algorithms solving composite…

Optimization and Control · Mathematics 2025-11-11 Nikita Doikov , Yurii Nesterov

We introduce a system of software tools that can automatically prove or discover geometric inequalities. The system, called GeoGebra Discovery, consisting of an extended version of GeoGebra, a controller web service realgeom, and the…

Logic · Mathematics 2022-01-04 Christopher W. Brown , Zoltán Kovács , Róbert Vajda

The Implicit Hitting Set (HS) approach has shown to be very effective for MaxSAT, Pseudo-boolean optimization and other boolean frameworks. Very recently, it has also shown its potential in the very similar Weighted CSP framework by means…

Artificial Intelligence · Computer Science 2025-01-15 Emma Rollón , Javier Larrosa , Aleksandra Petrova

Analytical solutions to differential equations offer exact, interpretable insight but are rarely available because discovering them requires expert intuition or exhaustive search of combinatorial spaces. We introduce SIGS, a neuro-symbolic…

Machine Learning · Computer Science 2026-05-22 Orestis Oikonomou , Levi Lingsch , Dana Grund , Siddhartha Mishra , Georgios Kissas

The so called generalized down-up algebras are revisited from a viewpoint of Gr\"obner basis theory. Particularly it is shown explicitly that generalized down-up algebras are solvable polynomial algebras (provided $\lambda\omega\ne 0$), and…

Rings and Algebras · Mathematics 2022-01-11 Rabigul Tuniyaz , Gulshadam Yunus

From the beginning of David Hestenes rediscovery of geometric algebra in the 1960s, outermorphisms have been a cornerstone in the mathematical development of GA. Many important mathematical formulations in GA can be expressed as…

Mathematical Software · Computer Science 2019-09-06 Ahmad Hosny Eid

This paper analyzes the structure of the set of nodal solutions of a class of one-dimensional superlinear indefinite boundary values problems with an indefinite weight functions in front of the spectral parameter. Quite astonishingly, the…

Analysis of PDEs · Mathematics 2020-05-21 Martin Fencl , Julián López-Gómez

The quadratic unconstrained binary optimization (QUBO) problem arises in diverse optimization applications ranging from Ising spin problems to classical problems in graph theory and binary discrete optimization. The use of preprocessing to…

Artificial Intelligence · Computer Science 2017-05-29 Fred Glover , Mark Lewis , Gary Kochenberger

A convergent iterative process is constructed for solving any solvable linear equation in a Hilbert space.

Numerical Analysis · Mathematics 2007-05-23 A. G. Ramm

We study stochastic Cubic Newton methods for solving general possibly non-convex minimization problems. We propose a new framework, which we call the helper framework, that provides a unified view of the stochastic and variance-reduced…

Optimization and Control · Mathematics 2025-12-19 El Mahdi Chayti , Nikita Doikov , Martin Jaggi

The robust truss topology optimization against the uncertain static external load can be formulated as mixed-integer semidefinite programming. Although a global optimal solution can be computed with a branch-and-bound method, it is very…

Optimization and Control · Mathematics 2019-01-25 Yoshihiro Kanno

Many systems of interest in cryptography consist of equations of the same degree. Under the assumption that the degree of regularity is finite, we prove upper bounds on the degree of regularity of a system of equations of the same degree,…

Cryptography and Security · Computer Science 2026-02-02 Giulia Gaggero , Elisa Gorla

There are few robust solutions to the doublet-triplet splitting problem in supersymmetric GUT theories. One of the more promising solutions is the Higgs as pseudo-Goldstone boson mechanism. In its minimal implementation, such a solution…

High Energy Physics - Phenomenology · Physics 2009-09-15 Csaba Csaki , Lisa Randall

Gaussian processes have become a promising tool for various safety-critical settings, since the posterior variance can be used to directly estimate the model error and quantify risk. However, state-of-the-art techniques for safety-critical…

Machine Learning · Computer Science 2022-07-22 Alexandre Capone , Armin Lederer , Sandra Hirche
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