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Gowers norms have been studied extensively both in the direct sense, starting with a function and understanding the associated norm, and in the inverse sense, starting with the norm and deducing properties of the function. Instead of…

Combinatorics · Mathematics 2015-03-17 Bernard Host , Bryna Kra

Efficient algorithms for many problems in optimization and computational algebra often arise from casting them as systems of polynomial equations. Blum, Shub, and Smale formalized this as Hilbert's Nullstellensatz Problem $HN_R$: given…

Computational Complexity · Computer Science 2025-10-28 Markus Bläser , Sagnik Dutta , Gorav Jindal

This is the third part of a series of four articles on weighted norm inequalities, off-diagonal estimates and elliptic operators. For $L$ in some class of elliptic operators, we study weighted norm $L^p$ inequalities for singular…

Classical Analysis and ODEs · Mathematics 2018-10-10 Pascal Auscher , José Maria Martell

Numerical Algebraic Geometry uses numerical data to describe algebraic varieties. It is based on the methods of numerical polynomial homotopy continuation, an alternative to the classical symbolic approaches of computational algebraic…

Algebraic Geometry · Mathematics 2011-11-23 Anton Leykin

Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. These hardware and software innovations promise to revolutionize solution times for complex problems. In this…

The design and implementation of parallel algorithms is a fundamental task in computer algebra. Combining the computer algebra system Singular and the workflow management system GPI-Space, we have developed an infrastructure for massively…

Algebraic Geometry · Mathematics 2020-10-16 Janko Boehm , Anne Frühbis-Krüger , Mirko Rahn

The work is devoted to the construction of a new type of intervals -- functional intervals. These intervals are built on the idea of expanding boundaries from numbers to functions. Functional intervals have shown themselves to be promising…

Numerical Analysis · Mathematics 2022-10-27 Dmitry A. Skorik

Linear programming (LP) is an extremely useful tool which has been successfully applied to solve various problems in a wide range of areas, including operations research, engineering, economics, or even more abstract mathematical areas such…

Data Structures and Algorithms · Computer Science 2022-09-26 Agniva Chowdhury , Gregory Dexter , Palma London , Haim Avron , Petros Drineas

This article demonstrates how an understanding of the geometry of a family of cost functions can be used to develop efficient numerical algorithms for real-time optimisation. Crucially, it is not the geometry of the individual functions…

Optimization and Control · Mathematics 2012-12-11 Jonathan H. Manton

A Geometric programming (GP) is a type of mathematical problem characterized by objective and constraint functions that have a special form. Many methods have been developed to solve large scale engineering design GP problems. In this paper…

Data Structures and Algorithms · Computer Science 2009-12-10 Dr. A. K. Ojha , K. K. Biswal

One of the greatest efforts of computational scientists is to translate the mathematical model describing a class of physical phenomena into large and complex codes. Many of these codes face the difficulty of implementing the mathematical…

Computational Engineering, Finance, and Science · Computer Science 2018-01-17 Edoardo Di Napoli , Elmar Peise , Markus Hrywniak , Paolo Bientinesi

We study homomorphism polynomials, which are polynomials that enumerate all homomorphisms from a pattern graph $H$ to $n$-vertex graphs. These polynomials have received a lot of attention recently for their crucial role in several new…

Computational Complexity · Computer Science 2020-11-17 Balagopal Komarath , Anurag Pandey , C. S. Rahul

Algebraic statistics uses tools from algebra (especially from multilinear algebra, commutative algebra and computational algebra), geometry and combinatorics to provide insight into knotty problems in mathematical statistics. In this survey…

Statistics Theory · Mathematics 2019-06-25 Marta Casanellas , Sonja Petrović , Caroline Uhler

We propose new estimates for the frontier of a set of points. They are defined as kernel estimates covering all the points and whose associated support is of smallest surface. The estimates are written as linear combinatio- ns of kernel…

Methodology · Statistics 2011-03-31 Guillaume Bouchard , Stéphane Girard , Anatoli Iouditski , Alexander Nazin

Nonnegative matrix factorization (NMF) has become a ubiquitous tool for data analysis. An important variant is the sparse NMF problem which arises when we explicitly require the learnt features to be sparse. A natural measure of sparsity is…

Machine Learning · Computer Science 2013-03-20 Vamsi K. Potluru , Sergey M. Plis , Jonathan Le Roux , Barak A. Pearlmutter , Vince D. Calhoun , Thomas P. Hayes

This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the…

Numerical Analysis · Mathematics 2013-10-22 Kenneth Lange , Hua Zhou

Expansion of higher transcendental functions in a small parameter are needed in many areas of science. For certain classes of functions this can be achieved by algebraic means. These algebraic tools are based on nested sums and can be…

High Energy Physics - Phenomenology · Physics 2015-06-25 Sven Moch , Peter Uwer , Stefan Weinzierl

We describe algebraic certificates of positivity for functions belonging to a finitely generated algebra of Borel measurable functions, with particular emphasis to algebras generated by semi-algebraic functions. In which case the standard…

Optimization and Control · Mathematics 2010-04-20 Jean-Bernard Lasserre , Mihai Putinar

We establish interval arithmetic as a practical tool for certification in numerical algebraic geometry. Our software HomotopyContinuation.jl now has a built-in function certify, which proves the correctness of an isolated nonsingular…

Algebraic Geometry · Mathematics 2024-07-12 Paul Breiding , Kemal Rose , Sascha Timme

Machine learning algorithms use error function minimization to fit a large set of parameters in a preexisting model. However, error minimization eventually leads to a memorization of the training dataset, losing the ability to generalize to…

Machine Learning · Computer Science 2018-03-16 Fernando Martin-Maroto , Gonzalo G. de Polavieja