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Related papers: Sparse non-SOS Putinar-type Positivstellens\"atze

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We show that any symmetric positive definite homogeneous matrix polynomial $M\in\R[x_1,...,x_n]^{m\times m}$ admits a piecewise semi-certificate, i.e. a collection of identites $M(x)=\sum_jf_{i,j}(x)U_{i,j}(x)^TU_{i,j}(x)$ where…

Rings and Algebras · Mathematics 2010-01-12 Ronan Quarez

To prove that a polynomial is nonnegative on R^n one can try to show that it is a sum of squares of polynomials (SOS). The latter problem is now known to be reducible to a semidefinite programming (SDP) computation much faster than…

Algebraic Geometry · Mathematics 2010-10-27 J. Maurice Rojas , Swaminathan Sethuraman

The prevalence of neural networks in society is expanding at an increasing rate. It is becoming clear that providing robust guarantees on systems that use neural networks is very important, especially in safety-critical applications. A…

Systems and Control · Electrical Eng. & Systems 2022-02-07 Matthew Newton , Antonis Papachristodoulou

This paper presents a constructive proof of the existence of a regular non-atomic strictly-positive measure on any second-countable non-atomic locally compact Hausdorff space. This construction involves a sequence of finitely-additive set…

Functional Analysis · Mathematics 2020-02-21 Jason Bentley

In recent years, much work has been devoted to a systematic study of polynomial identities certifying strict or non-strict positivity of a polynomial on a basic closed semialgebraic set. The interest in such identities originates not least…

Commutative Algebra · Mathematics 2009-05-27 Sabine Burgdorf , Claus Scheiderer , Markus Schweighofer

This paper introduces a notion of decomposition and completion of sum-of-squares (SOS) matrices. We show that a subset of sparse SOS matrices with chordal sparsity patterns can be equivalently decomposed into a sum of multiple SOS matrices…

Optimization and Control · Mathematics 2020-01-13 Yang Zheng , Giovanni Fantuzzi , Antonis Papachristodoulou

Gr{\"o}bner bases is one the most powerful tools in algorithmic non-linear algebra. Their computation is an intrinsically hard problem with a complexity at least single exponential in the number of variables. However, in most of the cases,…

Symbolic Computation · Computer Science 2019-02-04 Matías Bender , Jean-Charles Faugère , Elias Tsigaridas

The Sum-of-Squares (SoS) hierarchy, also known as Lasserre hierarchy, has emerged as a promising tool in optimization. However, it remains unclear whether fixed-degree SoS proofs can be automated [O'Donnell (2017)]. Indeed, there are…

Computational Complexity · Computer Science 2025-04-25 Alex Bortolotti , Monaldo Mastrolilli , Luis Felipe Vargas

Strassen's Positivstellensatz is a powerful but little known theorem on preordered commutative semirings satisfying a boundedness condition similar to Archimedeanicity. It characterizes the relaxed preorder induced by all monotone…

Algebraic Geometry · Mathematics 2021-02-03 Tobias Fritz

We give a general method for producing various effective Null and Positivstellens\"atze, and getting new Positivstellens\"atze in algebraically closed valued fields and ordered groups. These various effective Nullstellens\"atze produce…

Algebraic Geometry · Mathematics 2025-05-06 Michel Coste , Henri Lombardi , Marie-Françoise Roy

We show that existence of a global polynomial Lyapunov function for a homogeneous polynomial vector field or a planar polynomial vector field (under a mild condition) implies existence of a polynomial Lyapunov function that is a sum of…

Optimization and Control · Mathematics 2018-08-10 Amir Ali Ahmadi , Pablo A. Parrilo

A polynomial matrix inequality is a formula asserting that a polynomial matrix is positive semidefinite. Polynomial matrix optimization concerns minimizing the smallest eigenvalue of a symmetric polynomial matrix subject to a tuple of…

Optimization and Control · Mathematics 2025-06-06 Jared Miller , Jie Wang , Feng Guo

This paper discusses how to find the global minimum of functions that are summations of small polynomials (``small'' means involving a small number of variables). Some sparse sum of squares (SOS) techniques are proposed. We compare their…

Optimization and Control · Mathematics 2011-11-09 Jiawang Nie , James Demmel

In this paper, we prove that every SONC polynomial decomposes into a sum of nonnegative circuit polynomials with the same support, which reveals the advantage of SONC decompositions for certifying nonnegativity of sparse polynomials…

Combinatorics · Mathematics 2018-11-27 Jie Wang

We consider the problem of computing exact sums of squares (SOS) decompositions for certain classes of non-negative multivariate polynomials, relying on semidefinite programming (SDP) solvers. We provide a hybrid numeric-symbolic algorithm…

Symbolic Computation · Computer Science 2026-02-24 Victor Magron , Mohab Safey El Din

We show that contact-rich motion planning is also sparsity-rich when viewed as polynomial optimization (POP). We can exploit not only the correlative and term sparsity patterns that are general to all POPs, but also specialized sparsity…

Robotics · Computer Science 2025-09-08 Shucheng Kang , Guorui Liu , Heng Yang

Some sum of squares (SOS) polynomials admit decomposition certificates, or positive semidefinite Gram matrices, with additional structure. In this work, we use the structure of Gram matrices to relate the representation theory of $SL(2)$ to…

Optimization and Control · Mathematics 2024-07-30 Mitchell Tong Harris

Certifying nonnegativity of polynomials is a well-known NP-hard problem with direct applications spanning non-convex optimization, control, robotics, and beyond. A sufficient condition for nonnegativity is the Sum of Squares (SOS) property,…

Machine Learning · Computer Science 2025-10-16 Nico Pelleriti , Christoph Spiegel , Shiwei Liu , David Martínez-Rubio , Max Zimmer , Sebastian Pokutta

We present a new data structure for representation of polynomial variables in the parsing of sum-of-squares (SOS) programs. In SOS programs, the variables $s(x;Q)$ are polynomial in the independent variables $x$, but linear in the decision…

Optimization and Control · Mathematics 2022-09-05 Declan Jagt , Sachin Shivakumar , Peter Seiler , Matthew Peet

The second-order cone (SOC) is a class of simple convex cones and optimizing over them can be done more efficiently than with semidefinite programming. It is interesting both in theory and in practice to investigate which convex cones admit…

Optimization and Control · Mathematics 2025-04-29 Victor Magron , Jie Wang
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