GitHub

TSP Approximation Algorithms in Python

Here are a some implementations of various approximation algorithms for the optimal Travelling Salesperson Tour in 2D Euclidean Space. Additionally there are some helper algorithms such as Kruskal's ...
IEEE

Approximation Algorithm Applications in Artificial Intelligence: A Review

Abstract: The function of this study is devoted to aspects of approximation algorithms such as approximation problems and showing the relationship between approximation order, linear classification ...
IEEE

Approximation and Heuristic Algorithms for the Priority Facility Location Problem with Outliers

Abstract: In this paper, we propose the Priority Facility Location Problem with Outliers (PFLPO), which is a generalization of both the Facility Location Problem with Outliers (FLPO) and Priority ...
Microsoft

Stochastic Approximation and Reinforcement Learning: Hidden Theory and New Super-Fast Algorithms

Stochastic approximation algorithms are used to approximate solutions to fixed point equations that involve expectations of functions with respect to possibly unknown distributions. Among many ...
GitHub

SuiMikasa/ATA-Approximation-Algorithm

The ATA algorithm provides a novel approximation framework for analytic functions that cannot be expressed in closed-form via elementary or algebraic functions. It introduces a hybrid approximation ...
Queen Mary University of London

A polynomial-time approximation algorithm for the permanent of a matrix with non-negative entries

Mark Jerrum, Alistair Sinclair (UC Berkeley) and Eric Vigoda (Georgia Tech) received the Association for Computing Machinery (ACM) Test of Time Award at a virtual ceremony on Wednesday 23 June at the ...