Jan
1
2019
En 2019, le CNRS fête ses 80 ans (et le laboratoire I3S ses 30 ans). La délégation régionale du CNRS Côte d'Azur (DR20) dont fait partie le laboratoire propose des manifestations pendant toute l'année 2019.
ACTUALITÉS (tout voir)
Oct
21
2019
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2019
Dec
4
2019
Jun
1
2020
ACTUALITÉS
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Dec312019
En 2019, le CNRS fête ses 80 ans (et le laboratoire I3S ses 30 ans). La délégation régionale du CNRS Côte d'Azur (DR20) dont fait partie le laboratoire propose des manifestations pendant toute l'année 2019.
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Jun52020
The I3S LABORATORY
It's on the SophiaTech campus in the heart of the Sophia Antipolis technology park our laboratory conducts research in the field of information science and communication.
"Advancing knowledge, consider the economic and technological realities, while imagining tomorrow's solutions."
The I3S laboratory is one of the largest information and communication science laboratories in the French Riviera. it was one of first ones to settle down on Sophia Antipolis Science and Technology Park. It consists of a little less than 300 people. [+...]
In partnership with CNRS and INRIA, and numerous industrial collaborations, we work on the themes of innovative research at the cutting edge of science and technology: systems and networks ubiquitous, biology and digital health, modeling for environment interactions and practices. [+...]
The laboratory is organized in 4 teams:
COMRED team (French acronym for Communications, Networks, Embedded Systems, Distributed Systems)
MDSC team (French acronym for Discrete Models for Complex System)
SIS team (Signal, Image and Systems)
SPARKS team (Scalable and Pervasive softwARe and Knowledge Systems)
The 5 latest submissions recorded in HAL
Isma Belouah, Christine Nazaret, Pierre Petriacq, Sylvain Prigent, Camille Bénard, Virginie Mengin, Melisande Blein-Nicolas, Alisandra Denton, Thierry Balliau, Ségolène Augé, Olivier Bouchez, Jean-Pierre Mazat, Mark Stitt, Björn Usadel, Michel Zivy, Bertrand Beauvoit, Yves Gibon, Sophie Colombie.
Modeling Protein Destiny in Developing Fruit.
Plant Physiology, American Society of Plant Biologists, 2019, 180 (3), pp.1709-1724. ⟨10.1104/pp.19.00086⟩
Simone Parisotto, Luca Calatroni, Aurélie Bugeau, Nicolas Papadakis, Carola-Bibiane Schönlieb.
Variational Osmosis for Non-linear Image Fusion.
2019
Tien Cuong Phi, Alexandre Muzy, Patricia Reynaud-Bouret.
Event-Scheduling Algorithms with Kalikow Decomposition for Simulating Potentially Infinite Neuronal Networks.
SN Computer Science, Springer, 2020, 1 (1), ⟨10.1007/s42979-019-0039-3⟩
Thu Huong Nguyen, Andrea G. B. Tettamanzi.
An Evolutionary Approach to Class Disjointness Axiom Discovery.
2019 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2019, Oct 2019, Thessaloniki, Greece. pp.68-75, ⟨10.1145/3350546.3352502⟩
Alessandro Venerandi, Giovanni Fusco, Andrea G. B. Tettamanzi, David Emsellem.
A Machine Learning Approach to Study the Relationship between Features of the Urban Environment and Street Value.
Urban Science, MDPI, 2019, 3 (3), pp.100. ⟨10.3390/urbansci3030100⟩
FOCUS DU MOIS
N. Isoart and J.-C. Régin: Integration of Structural Constraints into TSP Models. 25th International Conference of Constraint Programming. LNCS, vol. 11802, pp. 284-299, Connecticut, USA 2019. Springer (2019)
Constraint Programming, Global constraint, TSP
Several models based on constraint programming have been proposed to solve the traveling salesman problem (TSP). The most efficient ones, such as the weighted circuit constraint (WCC), mainly rely on the Lagrangian relaxation of the TSP, based on the search for spanning tree or more precisely "1-tree". The weakness of these approaches is that they do not include enough structural constraints and are based almost exclusively on edge costs. The purpose of this paper is to correct this drawback by introducing the Hamiltonian cycle constraint associated with propagators. We propose some properties preventing the existence of a Hamiltonian cycle in a graph or, conversely, properties requiring that certain edges be in the TSP solution set. Notably, The authors design a propagator based on the research of k-cutsets. The combination of this constraint with the WCC constraint allows us to obtain, for the resolution of the TSP, gains of an order of magnitude for the number of backtracks as well as a strong reduction of the computation time.
