arXiv subjects

Isabella Lari

Publications and source records attributed to Isabella Lari.

4 recordsLinked to original sources

arXiv2022

A Linear Time Algorithm for Computing Max-Flow Vitality in Undirected Unweighted Planar Graphs

The vitality of an edge in a graph with respect to the maximum flow between two fixed vertices $s$ and $t$ is defined as the reduction of the maximum flow value caused by the removal of that edge. The max-flow vitality problem has already been efficiently solved for $st$-planar graphs but has remained open for general planar graphs. For the first time our result provides an optimal solution for general planar graphs although restricted to the case of unweighted planar graphs.

cs.DS↗

arXiv2021

Max-flow vitality in undirected unweighted planar graphs

We show a fast algorithm for determining the set of edges in a planar undirected unweighted graph, whose deletion reduces the maximum flow between two fixed vertices. This is a special case of the max flow vitality problem, that has been efficiently solved for general undirected graphs and st-planar graphs. The vitality of an edge of a graph with respect to the maximum flow between two fixed vertices s and t is defined as the reduction of the maximum flow caused by the removal of that edge. In this paper we show that the set of edges having vitality greater than zero in a planar undirected unweighted graph with n vertices can be found in O(n log n) worst-case time and O(n) space.

cs.DS↗

arXiv2018

Max flow vitality in general and $st$-planar graphs

The \emph{vitality} of an arc/node of a graph with respect to the maximum flow between two fixed nodes $s$ and $t$ is defined as the reduction of the maximum flow caused by the removal of that arc/node. In this paper we address the issue of determining the vitality of arcs and/or nodes for the maximum flow problem. We show how to compute the vitality of all arcs in a general undirected graph by solving only $2(n-1)$ max flow instances and, In $st$-planar graphs (directed or undirected) we show how to compute the vitality of all arcs and all nodes in $O(n)$ worst-case time. Moreover, after determining the vitality of arcs and/or nodes, and given a planar embedding of the graph, we can determine the vitality of a `contiguous' set of arcs/nodes in time proportional to the size of the set.

cs.DS↗

arXiv2014

On a Class of Parameters Estimators in Linear Models Dominating the Least Squares one, Based on Compressed Sensing Techniques

The estimation of parameters in a linear model is considered under the hypothesis that the noise, with finite second order statistics, can be represented in a given deterministic basis by random coefficients. An extended underdetermined design matrix is then considered and an estimator of the extended parameters is proposed with minimum $l_1$ norm. It is proved that if the noise variance is larger than a threshold, which depends on the unknown parameters and on the extended design matrix, then the proposed estimator of the original parameters dominates the least-squares estimator in the sense of the mean square error. A small simulation illustrates the behavior of the proposed estimator. Moreover it is shown experimentally that the proposed estimator can be convenient even if the design matrix is not known but only an estimate can be used. Furthermore the noise basis can eventually be used to introduce some prior information in the estimation process. These points are illustrated by simulation by using the proposed estimator for solving a difficult inverse ill-posed problem related to the complex moments of an atomic complex measure.

math.ST↗