13 citations · 25 across the 18 of their papers we have counts for
22 papers
Polynomial Time Learning-Augmented Algorithms for NP-hard Permutation Problems
Evripidis Bampis, Bruno Escoffier, Dimitris Fotakis +2
We consider a learning-augmented framework for NP-hard permutation problems. The algorithm has access to predictions telling, given a pair of elements, whether is before…
Improved FPT Approximation for Non-metric TSP
Evripidis Bampis, Bruno Escoffier, Michalis Xefteris
In the Traveling Salesperson Problem (TSP) we are given a list of locations and the distances between each pair of them. The goal is to find the shortest possible tour that visits…
Parsimonious Learning-Augmented Approximations for Dense Instances of -hard Problems
Evripidis Bampis, Bruno Escoffier, Michalis Xefteris
The classical work of (Arora et al., 1999) provides a scheme that gives, for any , a polynomial time approximation algorithm for dense instances of a family of $\mathcal…
Learning-Augmented Online TSP on Rings, Trees, Flowers and (almost) Everywhere Else
Evripidis Bampis, Bruno Escoffier, Themis Gouleakis +4
We study the Online Traveling Salesperson Problem (OLTSP) with predictions. In OLTSP, a sequence of initially unknown requests arrive over time at points (locations) of a metric sp…
Online TSP with Known Locations
Evripidis Bampis, Bruno Escoffier, Niklas Hahn +1
In this paper, we consider the Online Traveling Salesperson Problem (OLTSP) where the locations of the requests are known in advance, but not their arrival times. We study both the…
Canadian Traveller Problem with Predictions
Evripidis Bampis, Bruno Escoffier, Michalis Xefteris
In this work, we consider the -Canadian Traveller Problem (-CTP) under the learning-augmented framework proposed by Lykouris & Vassilvitskii. -CTP is a generalization of t…