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Given a finitely presented Graded Commutative Differential Algebra (GCDA), we present a method to compute its minimal model, together with a map that is a quasi-isomorphism up to a given degree. The method works by adding generators one by…

Algebraic Topology · Mathematics 2021-01-27 Victor Manero , Miguel Ángel Marco Buzunariz

Let G=(V,E) be a finite graph, and f:V->N be any function. The Local Search problem consists in finding a local minimum of the function f on G, that is a vertex v such that f(v) is not larger than the value of f on the neighbors of v in G.…

Quantum Physics · Physics 2007-05-23 Yves F. Verhoeven

We prove that the minimally displaced set of a relatively irreducible automorphism of a free splitting, situated in a deformation space, is uniformly locally finite. The minimally displaced set coincides with the train track points for an…

Group Theory · Mathematics 2020-04-17 Stefano Francaviglia , Armando Martino , Dionysios Syrigos

This paper presents a unified analysis framework that captures recent advances in the study of local-optimality characterizations for codes on graphs. These local-optimality characterizations are based on combinatorial structures embedded…

Information Theory · Computer Science 2012-08-15 Guy Even , Nissim Halabi

The iterative absorption method has recently led to major progress in the area of (hyper-)graph decompositions. Amongst other results, a new proof of the Existence conjecture for combinatorial designs, and some generalizations, was…

Combinatorics · Mathematics 2020-03-02 Ben Barber , Stefan Glock , Daniela Kühn , Allan Lo , Richard Montgomery , Deryk Osthus

A local weighted discontinuous Galerkin gradient discretization method for solving elliptic equations is introduced. The local scheme is based on a coarse grid and successively improves the solution solving a sequence of local elliptic…

Numerical Analysis · Mathematics 2018-07-30 Assyr Abdulle , Giacomo Rosilho de Souza

Dynamic Mode Decomposition (DMD) has emerged as a powerful tool for analyzing the dynamics of non-linear systems from experimental datasets. Recently, several attempts have extended DMD to the context of low-rank approximations. This…

Machine Learning · Statistics 2018-05-18 Patrick Héas , Cédric Herzet

As distributed systems increase in size, the need for scalable algorithms becomes more and more important. We argue that in the context of system identification, an essential building block of any scalable algorithm is the ability to…

Optimization and Control · Mathematics 2014-07-23 Nikolai Matni , Anders Rantzer

Let $R$ be a polynomial ring over a field. We describe the extremal rays and the facets of the cone of local cohomology tables of finitely generated graded $R$-modules of dimension at most two. Moreover, we show that any point inside the…

Commutative Algebra · Mathematics 2020-02-27 Alessandro De Stefani , Ilya Smirnov

We prove that the finite-difference based derivative-free descent (FD-DFD) methods have a capability to find the global minima for a class of multiple minima problems. Our main result shows that, for a class of multiple minima objectives…

Optimization and Control · Mathematics 2020-06-26 Xiaopeng Luo , Xin Xu , Daoyi Dong

Computing ground states of local Hamiltonians is a fundamental problem in condensed matter physics. We give the first randomized polynomial-time algorithm for finding ground states of gapped one-dimensional Hamiltonians: it outputs an…

Quantum Physics · Physics 2013-07-22 Zeph Landau , Umesh Vazirani , Thomas Vidick

The key to a robust and efficient implementation of a computational geometry algorithm is an efficient algorithm for detecting degenerate predicates. We study degeneracy detection in constructing the free space of a polyhedron that rotates…

Computational Geometry · Computer Science 2018-03-20 Victor Milenkovic , Elisha Sacks , Nabeel Butt

This paper presents a novel proof that for any convex cone, the size of conically independent generators is at most twice that of minimum cardinality generators. While this result is known for linear spaces, we extend it to general cones…

Optimization and Control · Mathematics 2024-12-03 Matthias Georg Mayer , Fabian von der Warth

We propose and analyze asymptotic proximal point (APP) methods to find the global minimizer for a class of nonconvex, nonsmooth, or even discontinuous multiple minima functions. The method is based on an asymptotic representation of…

Optimization and Control · Mathematics 2020-12-23 Xiaopeng Luo , Xin Xu , Herschel A. Rabitz

Let $P$ be a commutative Noetherian ring and $F$ be a self-dual acyclic complex of finitely generated free $P$-modules. Assume that $F$ has length four and $F_0$ has rank one. We prove that $F$ can be given the structure of a Differential…

Commutative Algebra · Mathematics 2021-03-17 Andrew R. Kustin

This work studies the linear approximation of high-dimensional dynamical systems using low-rank dynamic mode decomposition (DMD). Searching this approximation in a data-driven approach is formalised as attempting to solve a low-rank…

Machine Learning · Statistics 2021-08-23 Patrick Héas , Cédric Herzet

The fundamental matrix can be estimated from point matches. The current gold standard is to bootstrap the eight-point algorithm and two-view projective bundle adjustment. The eight-point algorithm first computes a simple linear least…

Optimization and Control · Mathematics 2014-03-20 Florian Bugarin , Adrien Bartoli , Didier Henrion , Jean-Bernard Lasserre , Jean-José Orteu , Thierry Sentenac

We study the structure of the algebra of polynomial invariants for the usual conjugation action of the complex special, SO_n, and general, O_n, orthogonal group on the space of traceless n by n complex matrices. (Note that these two…

Commutative Algebra · Mathematics 2009-09-01 Dragomir Z. Djokovic

A gradient-free deterministic method is developed to solve global optimization problems for Lipschitz continuous functions defined in arbitrary path-wise connected compact sets in Euclidean spaces. The method can be regarded as granular…

Optimization and Control · Mathematics 2021-07-15 Tao Qian , Lei Dai , Liming Zhang , Zehua Chen

We present a novel method called TESALOCS (TEnsor SAmpling and LOCal Search) for multidimensional optimization, combining the strengths of gradient-free discrete methods and gradient-based approaches. The discrete optimization in our method…

Optimization and Control · Mathematics 2025-05-20 Konstantin Sozykin , Andrei Chertkov , Anh-Huy Phan , Ivan Oseledets , Gleb Ryzhakov