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Smart premise selection is essential when using automated reasoning as a tool for large-theory formal proof development. A good method for premise selection in complex mathematical libraries is the application of machine learning to large…

Machine Learning · Computer Science 2014-01-07 Jesse Alama , Tom Heskes , Daniel Kühlwein , Evgeni Tsivtsivadze , Josef Urban

Given a graph $G$, the NP-hard Maximum Planar Subgraph problem (MPS) asks for a planar subgraph of $G$ with the maximum number of edges. There are several heuristic, approximative, and exact algorithms to tackle the problem, but---to the…

Data Structures and Algorithms · Computer Science 2016-08-29 Markus Chimani , Karsten Klein , Tilo Wiedera

Topological classification of the 4-manifolds bridges computation theory and physics. A proof of the undecidability of the homeomorphy problem for 4-manifolds is outlined here in a clarifying way. It is shown that an arbitrary Turing…

General Relativity and Quantum Cosmology · Physics 2007-05-23 James R. van Meter

A decision rule is epsilon-minimax if it is minimax up to an additive factor epsilon. We present an algorithm for provably obtaining epsilon-minimax solutions for a class of statistical decision problems. In particular, we are interested in…

This article is an investigation of a method of deriving a topology from a space and an elementary submodel containing it. We first define and give the basic properties of this construction, known as $X/M$. In the next section, we construct…

Logic · Mathematics 2015-04-08 Peter Burton

The binary Constraint Satisfaction Problem (CSP) is to decide whether there exists an assignment to a set of variables which satisfies specified constraints between pairs of variables. A binary CSP instance can be presented as a labelled…

Computational Complexity · Computer Science 2019-06-28 David A. Cohen , Martin C. Cooper , Peter G. Jeavons , Stanislav Zivny

Topology applied to real world data using persistent homology has started to find applications within machine learning, including deep learning. We present a differentiable topology layer that computes persistent homology based on level set…

This paper describes a new approach on optimization of constraint satisfaction problems (CSPs) by means of substituting sub-CSPs with locally consistent regular membership constraints. The purpose of this approach is to reduce the number of…

Artificial Intelligence · Computer Science 2019-08-19 Sven Löffler , Ke Liu , Petra Hofstedt

Networks are a commonly used mathematical model to describe the rich set of interactions between objects of interest. Many clustering methods have been developed in order to partition such structures, among which several rely on underlying…

Methodology · Statistics 2014-05-13 P. Latouche , E. Birmelé , C. Ambroise

We present and discuss applications of the category of probabilistic morphisms, initially developed in \cite{Le2023}, as well as some geometric methods to several classes of problems in statistical, machine and manifold learning which shall…

Machine Learning · Statistics 2025-05-08 Hông Vân Lê , Hà Quang Minh , Frederic Protin , Wilderich Tuschmann

The main purpose of this paper is to give a topological and symplectic classification of completely integrable Hamiltonian systems in terms of characteristic classes and other local and global invariants.

Differential Geometry · Mathematics 2007-05-23 Nguyen Tien Zung

We apply the local removable singularity theorem for minimal laminations and the local picture theorem on the scale of topology to obtain two descriptive results for certain possibly singular minimal laminations of $\mathbb{R}^3$. These two…

Differential Geometry · Mathematics 2016-11-24 William H. Meeks , Joaquin Perez , Antonio Ros

We study a semilinear elliptic equation with a pure power nonlinearity with exponent $p>1$, and provide sufficient conditions for the existence of positive solutions. These conditions involve expected exit times from the domain, $D$, where…

Analysis of PDEs · Mathematics 2023-09-26 Ma Elena Hernandez-Hernandez , Pablo Padilla-Longoria

Topological design of terrestrial networks for communication via satellites is studied in the paper. Quantitative model of the network cost-analysis minimizing the total transmission and switching cost is described. Several algorithms…

Networking and Internet Architecture · Computer Science 2010-02-19 Boris S. Verkhovsky

This paper addresses the pattern classification problem arising when available target data include some uncertainty information. Target data considered here is either qualitative (a class label) or quantitative (an estimation of the…

Machine Learning · Computer Science 2011-06-20 Emilie Niaf , Rémi Flamary , Carole Lartizien , Stéphane Canu

In this paper we present two new approaches for finding good starting solutions to the planar p-median problem. Both methods rely on a discrete approximation of the continuous model that restricts the facility locations to the given set of…

Optimization and Control · Mathematics 2020-04-14 Jack Brimberg , Zvi Drezner

Ranking (or top-k) and skyline queries are the most popular approaches used to extract interesting data from large datasets. The first one is based on a scoring function to evaluate and rank tuples. Its computation is fast, but it is…

Databases · Computer Science 2022-05-03 Carlo Bellacoscia

This is a typeset version of Alan Turing's Second World War research paper \textit{The Applications of Probability to Cryptography}. A companion paper \textit{Paper on Statistics of Repetitions} is also available in typeset form from arXiv…

History and Overview · Mathematics 2015-05-27 Ian Taylor

Let $M$ be a real $r\times c$ matrix and let $k$ be a positive integer. In the column subset selection problem (CSSP), we need to minimize the quantity $\|M-SA\|$, where $A$ can be an arbitrary $k\times c$ matrix, and $S$ runs over all…

Combinatorics · Mathematics 2017-01-12 Yaroslav Shitov

There has been a lot of interest in developing algorithms to extract clusters or communities from networks. This work proposes a method, based on blockmodelling, for leveraging communities and other topological features for use in a…

Social and Information Networks · Computer Science 2011-10-20 Leto Peel