M
Mauro Brunato
Researcher at University of Trento
Publications - 57
Citations - 1735
Mauro Brunato is an academic researcher from University of Trento. The author has contributed to research in topics: Local search (optimization) & Heuristics. The author has an hindex of 17, co-authored 57 publications receiving 1669 citations. Previous affiliations of Mauro Brunato include University of Florence.
Papers
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Journal ArticleDOI
Statistical learning theory for location fingerprinting in wireless LANs
Mauro Brunato,Roberto Battiti +1 more
TL;DR: Techniques and algorithms developed in the framework of Statistical Learning Theory are applied to the problem of determining the location of a wireless device by measuring the signal strength values from a set of access points (location fingerprinting), with the advantage of a low algorithmic complexity in the normal operating phase.
Book
Reactive Search and Intelligent Optimization
TL;DR: Reactive Search and Intelligent Optimization is an excellent introduction to the main principles of reactive search, as well as an attempt to develop some fresh intuition for the approaches.
Proceedings ArticleDOI
PILGRIM: A location broker and mobility-aware recommendation system
Mauro Brunato,Roberto Battiti +1 more
TL;DR: A mobility-aware recommendation system that considers the location of the user to filter recommended links is proposed, and the features of the PILGRIM mobile recommendation system are outlined together with a preliminary experimental evaluation of different metrics.
Book ChapterDOI
On Effectively Finding Maximal Quasi-cliques in Graphs
TL;DR: This work demonstrates how two previously existing definitions of quasi-cliques can be unified and how the resulting, more general quasi-Clique finding problem can be solved by extending two state-of-the-art stochastic local search algorithms for the classical maximum clique problem.
Transparent Location Fingerprinting for Wireless Services
Mauro Brunato,Csaba Kiss Kalló +1 more
TL;DR: Preliminary tests allow us to detect position on a map with an average uncertainty of two meters when using information gathered from three IEEE802.11 access points in an indoor environment composed of many rooms on a 625sqm area.