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This paper addresses the problem of enumerating all supported efficient solutions for a linear multi-objective integer minimum cost flow problem (MOIMCF). It derives an output-polynomial time algorithm to determine all supported efficient…

Optimization and Control · Mathematics 2025-06-02 David Könen , Michael Stiglmayr

A long-standing open question in Integer Programming is whether integer programs with constraint matrices with bounded subdeterminants are efficiently solvable. An important special case thereof are congruency-constrained integer programs…

Optimization and Control · Mathematics 2023-04-26 Martin Nägele , Richard Santiago , Rico Zenklusen

In this contribution we develop an efficient reduced order model for solving parametrized linear-quadratic optimal control problems with linear time-varying state system. The fully reduced model combines reduced basis approximations of the…

Numerical Analysis · Mathematics 2024-08-29 Hendrik Kleikamp , Lukas Renelt

Discrete-time robust optimal control problems generally take a min-max structure over continuous variable spaces, which can be difficult to solve in practice. In this paper, we extend the class of such problems that can be solved through a…

Optimization and Control · Mathematics 2024-04-30 Jad Wehbeh , Eric C. Kerrigan

A numerical method for the quasi-neutral two-fluid (QNTF) plasma model is described. The basic equations are ion and electron fluid equations and the Maxwell equations without displacement current. The neglect of displacement current is…

Computational Physics · Physics 2015-08-03 Takanobu Amano

Dominant areas of computer science and computation systems are intensively linked to the hypercube-related studies and interpretations. This article presents some transformations and analytics for some example algorithms and Boolean domain…

Discrete Mathematics · Computer Science 2024-02-05 Levon Aslanyan , Irina Arsenyan , Vilik Karakhanyan , Hasmik Sahakyan

The complexity class $NP$ can be logically characterized both through existential second order logic $SO\exists$, as proven by Fagin, and through simulating a Turing machine via the satisfiability problem of propositional logic SAT, as…

Logic · Mathematics 2014-10-21 Tuomo Kauranne

Typical performance of approximation algorithms is studied for randomized minimum vertex cover problems. A wide class of random graph ensembles characterized by an arbitrary degree distribution is discussed with some theoretical frameworks.…

Disordered Systems and Neural Networks · Physics 2016-11-10 Satoshi Takabe , Koji Hukushima

We study the 2-Disjoint Shortest Paths (2-DSP) problem: given a directed weighted graph and two terminal pairs $(s_1,t_1)$ and $(s_2,t_2)$, decide whether there exist vertex-disjoint shortest paths between each pair. Building on recent…

Data Structures and Algorithms · Computer Science 2025-10-09 Keerti Choudhary , Amit Kumar , Lakshay Saggi

Modeling real processes often results in several suitable models. In order to be able to distinguish, or discriminate, which model best represents a phenomenon, one is interested, e.g., in so-called T-optimal designs. These consist of the…

Optimization and Control · Mathematics 2022-08-30 David Mogalle , Philipp Seufert , Jan Schwientek , Michael Bortz , Karl-Heinz Küfer

Often machine learning and statistical models will attempt to describe the majority of the data. However, there may be situations where only a fraction of the data can be fit well by a linear regression model. Here, we are interested in a…

Machine Learning · Computer Science 2021-11-16 Brendan Juba , Leda Liang

This paper proposes a model, the linear model, for randomly generating logic programs with low density of rules and investigates statistical properties of such random logic programs. It is mathematically shown that the average number of…

Artificial Intelligence · Computer Science 2015-10-07 Kewen Wang , Lian Wen , Kedian Mu

In a classical scheduling problem, we are given a set of $n$ jobs of unit length along with precedence constraints, and the goal is to find a schedule of these jobs on $m$ identical machines that minimizes the makespan. Using the standard…

Data Structures and Algorithms · Computer Science 2023-12-07 Jesper Nederlof , Céline M. F. Swennenhuis , Karol Węgrzycki

We give a 3/2-approximation algorithm for stable matchings that runs in $O(m)$ time. The previously best known algorithm by McDermid has the same approximation ratio but runs in $O(n^{3/2}m)$ time, where $n$ denotes the number of people and…

Data Structures and Algorithms · Computer Science 2014-04-07 Katarzyna Paluch

In this paper, we propose two simple yet efficient computational algorithms to obtain approximate optimal designs for multi-dimensional linear regression on a large variety of design spaces. We focus on the two commonly used optimal…

Statistics Theory · Mathematics 2021-02-26 Jiangtao Duan , Wei Gao , Yanyuan Ma , Hon Keung Tony Ng

We show that the CNF satisfiability problem (SAT) can be solved in time $O^*(1.1199^{(d-2)n})$, where $d$ is either the maximum number of occurrences of any variable or the average number of occurrences of all variables if no variable…

Data Structures and Algorithms · Computer Science 2024-11-13 Sanjay Jain , Tzeh Yuan Neoh , Frank Stephan

We consider the fundamental algorithmic problem of finding a cycle of minimum weight in a weighted graph. In particular, we show that the minimum weight cycle problem in an undirected n-node graph with edge weights in {1,...,M} or in a…

Data Structures and Algorithms · Computer Science 2011-04-15 Liam Roditty , Virginia Vassilevska Williams

Efficient and accurate numerical algorithms are developed to solve a generalized Kirchhoff-Love plate model subject to three common physical boundary conditions: (i) clamped; (ii) simply supported; and (iii) free. We solve the model…

Numerical Analysis · Mathematics 2020-08-05 Duong T. A. Nguyen , Longfei Li , Hangjie Ji

Conditional Neural Processes (CNP; Garnelo et al., 2018) are an attractive family of meta-learning models which produce well-calibrated predictions, enable fast inference at test time, and are trainable via a simple maximum likelihood…

Machine Learning · Computer Science 2021-10-19 Stratis Markou , James Requeima , Wessel Bruinsma , Richard Turner

In threshold-linear networks (TLNs), a fixed point is called minimal if no proper subset of its support is also a fixed point. Curto et al (Advances in Applied Mathematics, 2024) conjectured that every stable fixed point of any TLN must be…

Neurons and Cognition · Quantitative Biology 2025-11-11 Jesse Geneson