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An extended range of energy stable flux reconstruction schemes, developed using a summation-by-parts approach, is presented on quadrilateral elements for various sets of polynomial bases. For the maximal order bases, a new set of correction…

Numerical Analysis · Mathematics 2022-06-03 Will Trojak , Rob Watson , Peter Vincent

We study the number of hamiltonian circuits, containing a fixed basis, and the number of hyperplanes, which do not contain a fixed basis in perfect matroid designs. Projective and affine finite geometries are considered as examples of such…

Combinatorics · Mathematics 2013-05-15 Wojciech Kordecki

The problem of solving tropical linear systems, a natural problem of tropical mathematics, has already proven to be very interesting from the algorithmic point of view: it is known to be in $NP\cap coNP$ but no polynomial time algorithm is…

Computational Complexity · Computer Science 2013-09-23 Alex Davydow

We can compare the expressiveness of neural networks that use rectified linear units (ReLUs) by the number of linear regions, which reflect the number of pieces of the piecewise linear functions modeled by such networks. However,…

Machine Learning · Computer Science 2019-12-17 Thiago Serra , Srikumar Ramalingam

The foundation of a matroid is a canonical algebraic invariant which classifies representations of the matroid up to rescaling equivalence. Foundations of matroids are pastures, a simultaneous generalization of partial fields and…

Combinatorics · Mathematics 2020-08-04 Matthew Baker , Oliver Lorscheid

We consider the fundamental Matroid Theory problem of finding a circuit in a matroid spanning a set T of given terminal elements. For graphic matroids this corresponds to the problem of finding a simple cycle passing through a set of given…

Data Structures and Algorithms · Computer Science 2016-07-20 Fedor V. Fomin , Petr A. Golovach , Daniel Lokshtanov , Saket Saurabh

Newton iteration (NI) is an almost 350 years old recursive formula that approximates a simple root of a polynomial quite rapidly. We generalize it to a matrix recurrence (allRootsNI) that approximates all the roots simultaneously. In this…

Computational Complexity · Computer Science 2017-10-10 Pranjal Dutta , Nitin Saxena , Amit Sinhababu

We show that lower bounds on the border rank of matrix multiplication can be used to non-trivially derandomize polynomial identity testing for small algebraic circuits. Letting $\underline{R}(n)$ denote the border rank of $n \times n \times…

Computational Complexity · Computer Science 2024-04-18 Robert Andrews

We provide a natural definition of an elliptic arrangement, extending the classical framework to an elliptic curve E with complex multiplication. We analyse the intersections of elements of the arrangement and their connected components as…

Combinatorics · Mathematics 2026-05-13 Luca Moci , Roberto Pagaria , Maddalena Pismataro , Alejandro Vargas

This work focuses on the analysis of fully connected feed forward ReLU neural networks as they approximate a given, smooth function. In contrast to conventionally studied universal approximation properties under increasing architectures,…

Machine Learning · Computer Science 2024-06-24 Erion Morina , Martin Holler

The computation of triangular decompositions are based on two fundamental operations: polynomial GCDs modulo regular chains and regularity test modulo saturated ideals. We propose new algorithms for these core operations relying on modular…

Symbolic Computation · Computer Science 2009-07-25 Xin Li , Marc Moreno Maza , Wei Pan

Pivoting methods are of vital importance for linear programming, the simplex method being the by far most well-known. In this paper, a primal-dual pair of linear programs in canonical form is considered. We show that there exists a sequence…

Optimization and Control · Mathematics 2019-08-29 Anders Forsgren , Fei Wang

We revisit the Universal Approximation Theorem(UAT) through the lens of the tropical geometry of neural networks and introduce a constructive, geometry-aware initialization for sigmoidal multi-layer perceptrons (MLPs). Tropical geometry…

Machine Learning · Statistics 2025-10-20 Yi-Shan Chu , Yueh-Cheng Kuo

We study symmetric arithmetic circuits and improve on lower bounds given by Dawar and Wilsenach (ArXiv 2020). Their result showed an exponential lower bound of the permanent computed by symmetric circuits. We extend this result to show a…

Computational Complexity · Computer Science 2020-09-24 Christian Engels

Networks are frequently studied algebraically through matrices. In this work, we show that networks may be studied in a more abstract level using results from the theory of matroids by establishing connections to networks by decomposition…

Combinatorics · Mathematics 2015-11-17 Konstantinos Papalamprou , Leonidas Pitsoulis

This paper proposes new factorizations for computing the Neumann series. The factorizations are based on fast algorithms for small prime sizes series and the splitting of large sizes into several smaller ones. We propose a different basis…

Numerical Analysis · Computer Science 2017-07-20 Vassil Dimitrov , Diego Coelho

In this note we characterize tropical bases as sets of circuits that by orthogonality determine the set of cocircuits of a simple matroid. Furthermore, we show that any circuit, which itself is closed, must be contained in any tropical…

Combinatorics · Mathematics 2024-06-21 Winfried Hochstättler

The minimum linear arrangement problem on a network consists of finding the minimum sum of edge lengths that can be achieved when the vertices are arranged linearly. Although there are algorithms to solve this problem on trees in polynomial…

Data Analysis, Statistics and Probability · Physics 2017-12-14 Juan Luis Esteban , Ramon Ferrer-i-Cancho , Carlos Gómez-Rodríguez

For the ordered set $[n]$ of $n$ elements, we consider the class $\Bscr_n$ of bases $B$ of tropical Pl\"ucker functions on $2^{[n]}$ such that $B$ can be obtained by a series of mutations (flips) from the basis formed by the intervals in…

Combinatorics · Mathematics 2010-11-15 Vladimir I. Danilov , Alexander V. Karzanov , Gleb A. Koshevoy

Due to the over-parameterization nature, neural networks are a powerful tool for nonlinear function approximation. In order to achieve good generalization on unseen data, a suitable inductive bias is of great importance for neural networks.…

Machine Learning · Computer Science 2021-11-17 Weiyang Liu , Rongmei Lin , Zhen Liu , Li Xiong , Bernhard Schölkopf , Adrian Weller