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The modular decomposition is a technique that applies but is not restricted to graphs. The notion of module naturally appears in the proofs of many graph theoretical theorems. Computing the modular decomposition tree is an important…

Discrete Mathematics · Computer Science 2009-12-10 Michel Habib , Christophe Paul

Polynomial factorization and root finding are among the most standard themes of computational mathematics. Yet still, little has been done for polynomials over quaternion algebras, with the single exception of Hamiltonian quaternions for…

Symbolic Computation · Computer Science 2023-05-04 Przemysław Koprowski

Sparse matrix factorization is a popular tool to obtain interpretable data decompositions, which are also effective to perform data completion or denoising. Its applicability to large datasets has been addressed with online and randomized…

Machine Learning · Statistics 2017-11-15 Arthur Mensch , Julien Mairal , Bertrand Thirion , Gaël Varoquaux

We present an effective method for computing parametric primary decomposition via comprehensive Gr\"obner systems. In general, it is very difficult to compute a parametric primary decomposition of a given ideal in the polynomial ring with…

Symbolic Computation · Computer Science 2024-08-29 Yuki Ishihara , Kazuhiro Yokoyama

Cyclotomic polynomials are basic objects in Number Theory. Their properties depend on the number of distinct primes that intervene in the factorization of their order, and the binary case is thus the first nontrivial case. This paper sees…

Number Theory · Mathematics 2024-11-07 Antonio Cafure , Eda Cesaratto

We investigate factorizability of a quadratic split quaternion polynomial. In addition to inequality conditions for existence of such factorization, we provide lucid geometric interpretations in the projective space over the split…

Rings and Algebras · Mathematics 2020-08-27 Daniel F. Scharler , Johannes Siegele , Hans-Peter Schröcker

For a wide variety of regularization methods, algorithms computing the entire solution path have been developed recently. Solution path algorithms do not only compute the solution for one particular value of the regularization parameter but…

Machine Learning · Computer Science 2009-03-30 Bernd Gärtner , Joachim Giesen , Martin Jaggi , Torsten Welsch

We prove that linearizing certain families of polynomial optimization problems leads to new functorial operations in real convex sets. We show that under some conditions these operations can be computed or approximated in ways amenable to…

Optimization and Control · Mathematics 2013-07-25 Mauricio Velasco

We construct a convergent family of outer approximations for the problem of optimizing polynomial functions over convex bodies subject to polynomial constraints. This is achieved by generalizing the polarization hierarchy, which has…

Optimization and Control · Mathematics 2024-06-17 Martin Plávala , Laurens T. Ligthart , David Gross

We show how one can obtain kink solutions of ordinary differential equations with polynomial nonlinearities by an efficient factorization procedure directly related to the factorization of their nonlinear polynomial part. We focus on…

Mathematical Physics · Physics 2009-11-10 H. C. Rosu , O. Cornejo-Perez

In this paper, we propose a framework based on sum-of-squares programming to design iterative first-order optimization algorithms for smooth and strongly convex problems. Our starting point is to develop a polynomial matrix inequality as a…

Optimization and Control · Mathematics 2018-09-25 Mahyar Fazlyab , Manfred Morari , Victor M. Preciado

We describe a novel analogue algorithm that allows the simultaneous factorization of an exponential number of large integers with a polynomial number of experimental runs. It is the interference-induced periodicity of "factoring"…

Quantum Physics · Physics 2016-03-14 Vincenzo Tamma

Let $f(x)$ be a separable polynomial over a local field. Montes algorithm computes certain approximations to the different irreducible factors of $f(x)$, with strong arithmetic properties. In this paper we develop an algorithm to improve…

Number Theory · Mathematics 2015-03-19 J. Guàrdia , E. Nart , S. Pauli

With the recent success of representation learning methods, which includes deep learning as a special case, there has been considerable interest in developing techniques that incorporate known physical constraints into the learned…

Machine Learning · Computer Science 2024-01-02 Harsha Vardhan Tetali , Joel B. Harley , Benjamin D. Haeffele

Matrix factorization methods are important tools in data mining and analysis. They can be used for many tasks, ranging from dimensionality reduction to visualization. In this paper we concentrate on the use of matrix factorizations for…

Machine Learning · Computer Science 2017-07-28 Sanjar Karaev , Pauli Miettinen

We investigate which polynomials can possibly occur as factors in the denominators of rational solutions of a given partial linear difference equation (PLDE). Two kinds of polynomials are to be distinguished, we call them /periodic/ and…

Symbolic Computation · Computer Science 2010-05-05 Manuel Kauers , Carsten Schneider

In this paper we develop techniques that eliminate the need of the Generalized Riemann Hypothesis (GRH) from various (almost all) known results about deterministic polynomial factoring over finite fields. Our main result shows that given a…

Computational Complexity · Computer Science 2009-02-08 Gábor Ivanyos , Marek Karpinski , Lajos Rónyai , Nitin Saxena

The radical solution of polynomials with rational coefficients is a famous solved problem. This paper found that it is a $\mathbb{NP}$ problem. Furthermore, this paper found that arbitrary $ \mathscr{P} \in \mathbb{P}$ shall have a one-way…

Computational Complexity · Computer Science 2024-05-28 Bojin Zheng , Weiwu Wang

We present a novel nonparametric algorithm for symmetry-based disentangling of data manifolds, the Geometric Manifold Component Estimator (GEOMANCER). GEOMANCER provides a partial answer to the question posed by Higgins et al. (2018): is it…

Machine Learning · Statistics 2020-11-19 David Pfau , Irina Higgins , Aleksandar Botev , Sébastien Racanière

We consider the Riemann-Hilbert factorization approach to solving the field equations of dimensionally reduced gravity theories. First we prove that functions belonging to a certain class possess a canonical factorization due to properties…

High Energy Physics - Theory · Physics 2018-04-04 G. L. Cardoso , J. C. Serra