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Giuseppe F. Italiano

Publications and source records attributed to Giuseppe F. Italiano.

40 records · Page 3Linked to original sources

Experimental Evaluation of Algorithms for the Food-Selection Problem

In this paper, we describe the result of our experiments on Algorithms for the Food-Selection Problem, which is the fundamental problem first stated and addressed in the seminal paper \cite{pigout}. Because the key aspect of any experimental evaluation is the \textbf{reproducibility}, we detail deeply the setup of all our experiments, thus leaving to the interested eater the opportunity to reproduce all the results described in this paper. More specifically, we describe all the answers we provided to the questions proposed in \cite{pigout}: Where can I have dinner tonight? What is the typical Roman cuisine that I should (not) miss? Where can I find the best coffee or gelato in town?

cs.DS↗

Personal data disclosure and data breaches: the customer's viewpoint

Every time the customer (individual or company) has to release personal information to its service provider (e.g., an online store or a cloud computing provider), it faces a trade-off between the benefits gained (enhanced or cheaper services) and the risks it incurs (identity theft and fraudulent uses). The amount of personal information released is the major decision variable in that trade-off problem, and has a proxy in the maximum loss the customer may incur. We find the conditions for a unique optimal solution to exist for that problem as that maximizing the customer's surplus. We also show that the optimal amount of personal information is influenced most by the immediate benefits the customer gets, i.e., the price and the quantity of service offered by the service provider, rather than by maximum loss it may incur. Easy spenders take larger risks with respect to low-spenders, but an increase in price drives customers towards a more careful risk-taking attitude anyway. A major role is also played by the privacy level, which the service provider employs to regulate the benefits released to the customers. We also provide a closed form solution for the limit case of a perfectly secure provider, showing that the results do not differ significantly from those obtained in the general case. The trade-off analysis may be employed by the customer to determine its level of exposure in the relationship with its service provider.

cs.CR↗

Improved Minimum Cuts and Maximum Flows in Undirected Planar Graphs

In this paper we study minimum cut and maximum flow problems on planar graphs, both in static and in dynamic settings. First, we present an algorithm that given an undirected planar graph computes the minimum cut between any two given vertices in O(n log log n) time. Second, we show how to achieve the same O(n log log n) bound for the problem of computing maximum flows in undirected planar graphs. To the best of our knowledge, these are the first algorithms for those two problems that break the O(n log n) barrier, which has been standing for more than 25 years. Third, we present a fully dynamic algorithm that is able to maintain information about minimum cuts and maximum flows in a plane graph (i.e., a planar graph with a fixed embedding): our algorithm is able to insert edges, delete edges and answer min-cut and max-flow queries between any pair of vertices in O(n^(2/3) log^3 n) time per operation. This result is based on a new dynamic shortest path algorithm for planar graphs which may be of independent interest. We remark that this is the first known non-trivial algorithm for min-cut and max-flow problems in a dynamic setting.

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Mantaining Dynamic Matrices for Fully Dynamic Transitive Closure

In this paper we introduce a general framework for casting fully dynamic transitive closure into the problem of reevaluating polynomials over matrices. With this technique, we improve the best known bounds for fully dynamic transitive closure. In particular, we devise a deterministic algorithm for general directed graphs that achieves $O(n^2)$ amortized time for updates, while preserving unit worst-case cost for queries. In case of deletions only, our algorithm performs updates faster in O(n) amortized time. Our matrix-based approach yields an algorithm for directed acyclic graphs that breaks through the $O(n^2)$ barrier on the single-operation complexity of fully dynamic transitive closure. We can answer queries in $O(n^ε)$ time and perform updates in $O(n^{ω(1,ε,1)-ε}+n^{1+ε})$ time, for any $ε\in[0,1]$, where $ω(1,ε,1)$ is the exponent of the multiplication of an $n\times n^ε$ matrix by an $n^ε\times n$ matrix. The current best bounds on $ω(1,ε,1)$ imply an $O(n^{0.58})$ query time and an $O(n^{1.58})$ update time. Our subquadratic algorithm is randomized, and has one-side error.

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