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Accurate modelling of the joint extremal dependence structure within a stationary time series is a challenging problem that is important in many applications.\ Several previous approaches to this problem are only applicable to certain types…

Methodology · Statistics 2023-03-09 Graeme Auld , Ioannis Papastathopoulos

The degree-based entropy of a graph is defined as the Shannon entropy based on the information functional that associates the vertices of the graph with the corresponding degrees. In this paper, we study extremal problems of finding the…

Combinatorics · Mathematics 2021-09-01 Yanni Dong , Maximilien Gadouleau , Pengfei Wan , Shenggui Zhang

We consider high-order splitting schemes for large-scale differential Riccati equations. Such equations arise in many different areas and are especially important within the field of optimal control. In the large-scale case, it is critical…

Optimization and Control · Mathematics 2018-08-14 Tony Stillfjord

We propose an exact algorithm for solving the longest simple path problem between two given vertices in undirected weighted graphs. By using graph partitioning and dynamic programming, we obtain an algorithm that is significantly faster…

Data Structures and Algorithms · Computer Science 2019-05-10 Kai Fieger , Tomas Balyo , Christian Schulz , Dominik Schreiber

Column generation and branch-and-price are leading methods for large-scale exact optimization. Column generation iterates between solving a master problem and a pricing problem. The master problem is a linear program, which can be solved…

Optimization and Control · Mathematics 2025-10-17 Ryo Kuroiwa , Edward Lam

We rewrite the standard nodal virtual element method as a generalised gradient method. This re-formulation allows for computing a reliable and efficient error estimator by locally reconstructing broken fluxes and potentials on elemental…

Numerical Analysis · Mathematics 2025-03-18 Théophile Chaumont-Frelet , Joscha Gedicke , Lorenzo Mascotto

This paper presents a universal numerical scheme tailored for tackling linear integral, integro-differential, and both initial and boundary value problems of ordinary differential equations. The numerical scheme is readily adapted for…

General Mathematics · Mathematics 2026-01-23 Vladimir Kryzhniy

We study the problem of approximating the Ising model partition function with complex parameters on bounded degree graphs. We establish a deterministic polynomial-time approximation scheme for the partition function when the interactions…

Quantum Physics · Physics 2019-07-12 Ryan L. Mann , Michael J. Bremner

We present new deterministic algorithms for several cases of the maximum rank matrix completion problem (for short matrix completion), i.e. the problem of assigning values to the variables in a given symbolic matrix as to maximize the…

Data Structures and Algorithms · Computer Science 2014-07-11 Gábor Ivanyos , Marek Karpinski , Nitin Saxena

We describe a dynamic programming algorithm for computing the marginal distribution of discrete probabilistic programs. This algorithm takes a functional interpreter for an arbitrary probabilistic programming language and turns it into an…

Artificial Intelligence · Computer Science 2012-09-12 Andreas Stuhlmüller , Noah D. Goodman

We consider the problem of finding a subgraph of a given graph which maximizes a given function evaluated at its degree sequence. While the problem is intractable already for convex functions, we show that it can be solved in polynomial…

Combinatorics · Mathematics 2020-11-10 Shmuel Onn

It is shown in "SIAM J. Sci. Comput. 39 (2017):B424-B441" that free-form curves used in computer aided geometric design can usually be represented as the solutions of linear differential systems and points and derivatives on the curves can…

Numerical Analysis · Computer Science 2019-11-05 Xunnian Yang , Jialin Hong

Many optimization problems can be naturally represented as (hyper) graphs, where vertices correspond to variables and edges to tasks, whose cost depends on the values of the adjacent variables. Capitalizing on the structure of the graph,…

Logic in Computer Science · Computer Science 2015-04-13 Nicklas Hoch , Ugo Montanari , Matteo Sammartino

In the 1960s, Erd\H{o}s and his cooperators initiated the research of the maximum numbers of edges in a graph or a planar graph on $n$ vertices without $k$ edge-disjoint cycles. This problem had been solved for $k\leq4$. As pointed out by…

Combinatorics · Mathematics 2022-07-21 Zhai Mingqing , Liu Muhuo

This paper presents a partial differential equation framework for deep residual neural networks and for the associated learning problem. This is done by carrying out the continuum limits of neural networks with respect to width and depth.…

Analysis of PDEs · Mathematics 2020-08-25 Hailiang Liu , Peter Markowich

In order to prove numerically the global existence and uniqueness of smooth solutions of a fourth order, nonlinear PDE, we derive rigorous a-posteriori upper bounds on the supremum of the numerical range of the linearized operator. These…

Analysis of PDEs · Mathematics 2017-08-22 Christian Nolde , Dirk Blömker

In this article we introduce a simple tool to derive polynomial upper bounds for the probability of observing unusually large maximal components in some models of random graphs when considered at criticality. Specifically, we apply our…

Probability · Mathematics 2022-02-01 Umberto De Ambroggio

This paper proposes a polynomial-time algorithm to construct the monotone stepwise curve that minimizes the sum of squared errors with respect to a given cloud of data points. The fitted curve is also constrained on the maximum number of…

Optimization and Control · Mathematics 2021-07-01 Víctor Bucarey , Martine Labbé , Juan M. Morales , Salvador Pineda

We consider polynomials of degree $d$ with only real roots and a fixed value of discriminant, and study the problem of minimizing the absolute value of polynomials at a fixed point off the real line. There are two explicit families of…

Complex Variables · Mathematics 2019-03-04 Arturas Dubickas , Igor Pritsker

Developing efficient numerical algorithms for the solution of high dimensional random Partial Differential Equations (PDEs) has been a challenging task due to the well-known curse of dimensionality. We present a new solution framework for…

Machine Learning · Computer Science 2019-10-17 Mohammad Amin Nabian , Hadi Meidani
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