Séminaire d'Automatique du Plateau de Saclay : Message-passing computation of the harmonic influence in social networks

Séminaire le 21 Novembre 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Paolo Frasca (CNRS Researcher, NeCS team, GIPSA-lab, Grenoble, France).


The harmonic influence is a measure of node influence in social networks that quantifies the ability of a leader node to alter the average opinion of the network, acting against an adversary field node. The definition of harmonic influence assumes linear interactions between the nodes described by an undirected weighted graph; its computation requires to solve, for every node, a discrete Dirichlet problem associated to a grounded Laplacian. In this talk, I will describe a message-passing distributed algorithm that concurrently computes the harmonic influence of all nodes and provide a convergence analysis for it. The algorithm converges asymptotically, under the only assumption of the interaction Laplacian being symmetric. However, the convergence value does not in general coincide with the harmonic influence: simulations show that when the network has a larger number of cycles, the algorithm becomes slower and less accurate, but nevertheless provides a useful approximation. Simulations also indicate that the symmetry condition is not necessary for convergence and that performance (both in terms of speed and asymptotical error) scales well in the number of nodes of the graph.

Bio. Paolo Frasca received the Ph.D. degree in Mathematics for Engineering Sciences from Politecnico di Torino, Torino, Italy, in 2009. Between 2008 and 2013, he has held research and visiting positions at the University of California, Santa Barbara (USA), at the IAC-CNR (Rome, Italy), at the University of Salerno (Italy), and at the Politecnico di Torino. From 2013 to 2016, he has been an Assistant Professor at the University of Twente in Enschede, the Netherlands. In October 2016 he joined the CNRS as Researcher: he is currently affiliated with GIPSA-lab in Grenoble, France.
His research interests are in the theory of network systems and cyber-physical systems, with applications to robotic, sensor, infrastructural, and social networks. On these topics, Dr. Frasca has (co)authored more than fifty journal and conference papers and has given invited talks at several international institutions and events, including the 2015 SICE International Symposium on Control Systems in Tokyo. He is a recipient of the 2013 SIAG/CST Best SICON Paper Prize. He has been a visiting professor at the LAAS, Toulouse, France in 2016 and at the University of Cagliari, Italy in 2017.
Dr. Frasca has served as Associate Editor of several international conferences, including IEEE CDC, ACC, ECC, MTNS, IFAC NecSys, and is currently serving as Associate Editor for the International Journal of Robust and Nonlinear Control, the Asian Journal of Control, and the IEEE Control Systems Letters.

S³: Estimation de l’intensité d’un processus de comptage en grande dimension

Séminaire le 17 Novembre 2017, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Sarah Lemler (MICS, CentraleSupélec, Gif)


Nous cherchons à estimer/apprendre le lien entre des covariables en grande dimension et l’intensité
avec laquelle des événements se produisent (décès, crises d’asthme, achats, notes de blogs, sinistres...).

Pour répondre à cette problématique, nous proposons deux approches pour estimer l’intensité
de sauts d’un processus de comptage en présence d’un grand nombre de covariables. D’abord, nous
considérons une intensité non-paramétrique et nous l’estimons par le meilleur modèle de Cox. Nous
considérons alors une procédure Lasso, spécifique à la grande dimension, pour estimer simultanément
les deux paramètres inconnus du meilleur modèle de Cox approximant l’intensité. Nous prouvons
des inégalités oracles non-asymptotiques pour l’estimateur Lasso obtenu.

Dans une seconde partie, nous supposons que l’intensité satisfait un modèle de Cox. Nous proposons
deux procédures en deux étapes pour estimer les paramètres inconnus du modèle de Cox. La
première étape est commune aux deux procédures, il s’agit d’estimer le paramètre de régression en
grande dimension via une procédure Lasso. Le risque de base est ensuite estimé soit par sélection de
modèles, soit par un estimateur à noyau avec une fenêtre choisie par la méthode de Goldenshluger
et Lepski. Nous établissons des inégalités oracles non-asymptotiques pour les deux estimateurs du
risque de base ainsi obtenus. Nous menons une étude comparative de ces estimateurs sur des données
simulées, et enfin, nous appliquons les procédures implémentées à une base de données sur le cancer
du sein.

Séminaire d'Automatique du Plateau de Saclay : Distributed Abstractions for Multi-Agent Systems Based on Robust Multi-Agent Control

Séminaire le 7 Novembre 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Dimitris Boskos (Postdoctoral researcher, Department of Automatic Control, School of Electrical Engineering, Royal Institute of Technology (KTH), Stockholm, Sweden)


High level task planning for multi-agent systems constitutes a research area which has gained an emerging attention during the last two decades. While the agents' coordination is in principle based on the design of continuous interaction protocols, the derivation of high level plans requires a discrete representation of their dynamic behavior, also called abstraction, in order to leverage algorithmic tools for the plan synthesis.    

In this talk we discuss the derivation of such abstractions for agents with continuous dynamics, comprising of feedback interconnection terms and additive bounded inputs, which provide the ability for high level planning under the coupled constraints. These dynamics are also motivated by multi-agent coordination protocols which are robust with respect to the additional input part. We will present such a cooperative control framework, which guarantees that network connectivity is robustly maintained with respect to bounded additive inputs. Furthermore, a modification of the feedback design ensures forward invariance of the agents' trajectories inside a convex workspace, without affecting the inputs' robustness bounds.

In order to derive the agents' distributed symbolic models, we determine space-time discretizations which establish that each agent's abstraction has at least one outgoing transition from every discrete state. The symbolic model of each agent is based on the knowledge of its neighbors' discrete positions and the transitions are performed through hybrid control laws, which can drive the agent to its possible successor states. As an extension of these results we also consider a varying degree of decentralization and build each abstract model based on discrete information up to a tunable distance in the communication graph. Finally, we discuss the derivation of online  abstractions, by discretizing over approximations of the agents' reachable sets over a bounded time horizon.

Bio. Dimitris Boskos was born in Athens, Greece in 1981. He has received the Diploma in Mechanical Engineering from the National Technical University of Athens (NTUA), Greece, in 2005, the M.Sc. in Applied Mathematics from the NTUA in 2008 and the Ph.D. in Applied mathematics from the NTUA in 2014. Since August 2014, he is a Postdoctoral Researcher at the Department of Automatic Control, School of Electrical Engineering, Royal Institute of Technology (KTH), Stockholm, Sweden. His research interests include distributed control of multi-agent systems, formal verification and observer design for nonlinear systems.

S³: Selective Updating and Cooperation for Distributed Estimation and Detection

Séminaire le 26 Octobre 2017, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Marcello Campos (COPPE/UFRJ)


This talk discusses selective update and cooperation strategies for parameter estimation and event detection in distributed adaptive sensor networks. We investigate a set-membership filtering approach which results in reduced complexity for updating parameter estimates at each network node. We explore cooperation strategies in adaptive distributed sensor networks for reduction in information exchange between cooperating nodes, and search for an optimal strategy to obtain consensus estimates.

Bio: This talk discusses selective update and cooperation strategies for parameter estimation and event detection in distributed adaptive sensor networks. We investigate a set-membership filtering approach which results in reduced complexity for updating parameter estimates at each network node. We explore cooperation strategies in adaptive distributed sensor networks for reduction in information exchange between cooperating nodes, and search for an optimal strategy to obtain consensus estimates.

Séminaire d'Automatique du Plateau de Saclay : Optimal control problems with oscillations, concentrations, and discontinuities.

Séminaire le 19 Octobre 2017, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Didier Henrion (CNRS Senior Researcher, LAAS-CNRS & Professor, Faculty of Electrical Engineering, Czech Technical University)


Optimal control problems with oscillation (chattering controls) and concentration (impulsive controls) can have integral performance criteria such that concentration of the control signal occurs at a discontinuity of the state signal. Techniques from functional analysis (extensions of DiPerna-Majda measures from the partial differential equations literature) are developed to give a precise meaning of the integral cost and to allow for the sound application of numerical methods. We show how this can be achieved for the Lasserre hierarchy of semidefinite programming relaxations. This includes in particular the use of compactification techniques allowing for unbounded time, state and control.

Bio. Didier Henrion is a CNRS Senior Researcher at LAAS, an engineering laboratory in Toulouse, France. He is also a Professor at the Faculty of Electrical Engineering at the Czech Technical University in Prague, Czechia. Since 1994 he has been developing constructive tools for addressing mathematical problems arising from systems control and optimization.

Séminaire d'Automatique du plateau de Saclay : Stabilization of nonlinear infinite-dimensional systems subject to saturations

Séminaire le 19 Octobre 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Swann Marx (Postdoctoral researcher, LAAS-CNRS)


This presentation provides contributions in stabilization methods for nonlinear dynamical systems. In particular, it focuses on the analysis of infinite-dimensional systems subject to saturated inputs.

In the first part, we will introduce a more general class of saturations than the one known for finite-dimensional systems. When bounding a linear stabilizing feedback law with such nonlinearity, a well-posedness result together with an attractivity result will be stated for systems whose open-loop is described by (possibly nonlinear) operators generating strongly continuous semigroup of contractions. The attractivity result will be proved by using the LaSalle's Invariance Principle together with some precompactness properties. 

In the second part, a particular nonlinear partial differential equation is studied, namely the Korteweg-de Vries equation, that models long waves in water of relatively shallow depth. A control actuating on a small part of the channel will be considered. This control will be modified with two different types of saturations. The attractivity result will be proved by using Lyapunov argument and a contradiction argument. Finally, the results will be illustrated with some numerical simulations.

Bio. Swann Marx graduated in 2014 from "Ecole Supérieure de Cachan", France. He got his Ph.D. in the Departement of Automatic at the GIPSA-lab, in Grenoble, France. He is currently a postdoctoral researcher at the LAAS-CNRS, in Toulouse, France. His main research interests are stabilization of partial differential equations with constrained inputs, output feedback stabilization and optimal control of nonlinear partial differential equations.

Inertia in inverter-dominated power networks.

Séminaire le 13 Octobre 2017, 15h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Pooya MONSHIZADEH (PhD student at University of Groningen, The Netherlands)


Along with the emergence of the renewable energy sources in power networks, and consequently the increasing usage of power converters, new issues and concerns regarding stability of the grid have arisen. Recently, the problem of low inertia of inverter dominated systems has been extensively investigated. In this talk, I address the problem of stability and frequency regulation of a recently proposed inverter. In this type of inverter, the DC-side capacitor emulates the inertia of a synchronous generator. First, I discuss remodeling the dynamics from the electrical power perspective. Using this model, it can be shown that the system is stable if connected to a constant power load, and the frequency can be regulated by a suitable choice of the controller. I elaborate the analysis of the stability of a network of inverters with capacitive inertia, and show that frequency regulation can be achieved by using an
appropriate controller design.

A View of Information-Estimation Relations in Gaussian Networks

Séminaire le 9 Octobre 2017, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Prof. Shlomo Shamai (Andrew and Erna Viterbi Department of Electrical Engineering)


This talk will focus on the recent applications of Information-Estimation Relations to Gaussian Networks. In the first part of the talk, we will go over recent connections between estimation theoretic and information theoretic measures. The estimation theoretic measures that would
be of importance to us are the Minimum Means p-th Error (MMPE) and its special case the Minimum Mean Square Error (MMSE). As will be demonstrated, the MMSE can be very useful in bounding mutual information via the I-MMSE relationship of Guo-Shamai-Verdu, and the MMPE can be used to bound the conditional entropy via the moment entropy inequality. In the second part of the talk, we will discuss several applications of Information-Estimation Relations in Gaussian noise networks. As the first application, we show how the I-MMSE relationship can be used to determine the behavior, for every signal-to-noise ratio (SNR), of the mutual information and the MMSE of the transmitted codeword for the setting of the Gaussian Broadcast Channel and the Gaussian Wiretap Channel. As a second application, the notion of the MMPE is used to generalize the Ozarow-Wyner lower bound on the mutual information for discrete inputs on Gaussian noise channels. A short outlook of future applications concludes the presentation.

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This work is in collaboration with R. Bustin, A. Dytso, H. Vincent Poor, Daniela Tuninetti, Natasha Devroye, and it is supported by the European Union's Horizon 2020 Research And Innovation Programme, grant agreement no. 694630.

S³ seminar : Big Data in the Social Sciences: Statistical methods for multi-source high-dimensional data

Séminaire le 6 Octobre 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Katrijn Van Deun (Tilburg University, the Netherlands)


Research in the behavioural and social sciences has entered the era of big data: Many detailed measurements are taken and multiple sources of information are used to unravel complex multivariate relations. For example, in studying obesity as the outcome of environmental and genetic influences, researchers increasingly collect survey, dietary, biomarker and genetic data from the same individuals.

Although linked more-variables-than-samples (called high-dimensional) multi-source data form an extremely rich resource for research, extracting meaningful and integrated information is challenging and not appropriately addressed by current statistical methods. A first problem is that relevant information is hidden in a bulk of irrelevant variables with a high risk of finding incidental associations. Second, the sources are often very heterogeneous, which may obscure apparent links between the shared mechanisms.

In this presentation we will discuss the challenges associated to the analysis of large scale multi-source data and present state-of-the-art statistical approaches to address the challenges.

Combined Optimal Activation and Transmission Control in Delay Tolerant Network

Séminaire le 4 Octobre 2017, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Amar Prakash Azad, Inria Sophia Antipolis


Generalized Secrecy Capacity

Séminaire le 2 Octobre 2017, 11h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Matthieu Bloch


On the Degrees of Freedom of MISO Broadcast Channels with Partial CSIT

Séminaire le 20 Septembre 2017, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Dr. Hamdi Joudeh (Imperial College London)


The multiple-input-single-output (MISO) broadcast channel (BC), in which a multi-antenna transmitter communicates with multiple uncoordinated single-antenna receivers, is an essential building block of modern wireless networks. In this channel, multiuser interference management is naturally carried out at the transmitter. This in turn requires highly accurate and up-to-date channel state information at the transmitter (CSIT), which is not always available in practice. While it is understood that the MISO BC is sensitive to CSIT inaccuracies, the capacity under such conditions remains largely a mystery. Hence, it is natural to resort to coarse approximations, e.g. the Degrees of Freedom (DoF), when studying such challenging problems. In this talk, I will review some recent (and not so recent) results in DoF studies of the MISO BC when only partial instantaneous CSIT is available. I will be focusing on tools used to derive achievability and converse result. I will also present some new DoF results for parallel MISO BCs (e.g. OFDM) with partial CSIT. Implications, insights and open problems are also discussed.

Bio: Hamdi Joudeh is a postdoctoral research associate in the Communications and Signal Processing Group, Department of Electrical and Electronic Engineering at Imperial College London. He received his PhD in Electrical Engineering and MSc in Communications and Signal Processing from Imperial College London, UK, in 2016 and 2011 respectively. His research interests are in the areas of wireless communications and multiuser information theory. He is currently serving as an associate editor for the EURASIP Journal on Wireless Communications and Networking.

Séminaire d’Automatique du plateau de Saclay : Non-Markovian Quantum Feedback Networks

Séminaire le 30 Juin 2017, 11h00 à INRIA Paris (Salle A115)
John Gough (Institute of Mathematics and Physics, Aberystwyth University)


We will recall the theory of Markovian Quantum feedback Networks, and explain some recent models with non-Markovian behaviour coming from physical requirements.

The concept of a controlled flow of a dynamical system, especially when the controlling process feeds information back about the system, is of central importance in control engineering, and we build on the ideas of by Bouten and van Handel to develop a general theory of quantum feedback. We elucidate the relationship between the controlling processes Z and the measured process Y, and to this end make a distinction between what we call the input picture and the output picture.

The theory is general enough to include a modulating filter which processes the measurement readout Y before returning to the system. This opens up the prospect of applying very general engineering feedback control techniques to open quantum systems in a systematic manner, and we consider a number of specific modulating filter problems.

 

Bio. John E. Gough was born in Drogheda, Ireland, in 1967. He received the B.Sc. and M.Sc. in Mathematical Sciences and the Ph.D. degree in Mathematical Physics from the National University of Ireland, Dublin, in 1987, 1988 and 1992 respectively. He was reader in Mathematical Physics at the Department of Mathematics and Computing, Nottingham-Trent University, up until 2007. He then joined the Institute of Mathematics and Physics at Aberystwyth University as established chair of Mathematics. He has held visiting positions at the University of Rome Tor Vergata, EPFL Lausanne, UC Santa Barbara and the Hong Kong Polytechnic University. His research interests include quantum probability, measurement and control of open quantum dynamical systems, and quantum feedback networks.

Séminaire d'Automatique du Plateau de Saclay : Quantum reservoir engineering to control light with atoms.

Séminaire le 20 Juin 2017, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Alain Sarlette (QUANTIC Lab, INRIA Paris & SYSTeMS research group, Ghent University)


This talk will give a simple introduction to a quantum stabilization technique called "reservoir engineering", which builds on the dissipation induced on a target system by its interaction with an open auxiliary system. We will introduce the technique, recall some older results obtained in our group and finally present our latest results in which we study the effect on the target system, of entanglement "in time" in the auxiliary system. This is joint work with my postdoc Zibo Miao.

Bio. Alain Sarlette has an engineering degree (applied physics) and a PhD (systems and control theory) from the University of Liège, Belgium. He has been a visiting researcher at Princeton University, Mines Paris-Tech, IIT Bombay among others. He is currently assistant professor at Ghent University (Belgium) and Senior Researcher (CR1) at INRIA Paris in the QUANTIC lab. His research interests include nonlinear and geometric control, coordination algorithms, and mainly algorithms and control for quantum technologies.

Séminaire d'Automatique du plateau de Saclay : Some Mathematical and Numerical questions on the Lindblad equation. Application to Quantum Control.

Séminaire le 20 Juin 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Claude Le Bris (Ecole des Ponts & Inria)


We overview a series of joint works with P. Rouchon (Mines de Paris) and other collaborators devoted to the mathematical analysis and the numerical simulation of high-dimensional Lindblad equations. These equations rule the time evolution of density matrices of open quantum systems. The numerical techniques we present aim
at adaptively constructing a low-rank approximation of the density matrices, deriving an evolution equation for this reduced model, and using it as a surrogate model for the original evolution. Alternately, using that reduced model, we also consider and improve advanced Monte-Carlo type techniques that simulate the stochastic system of equations equivalent to the Lindblad equation. The practically relevant setting where we test our approaches arises in stabilization/control problems for quantum optics and circuits. We believe that, interestingly, our approaches may be readily adapted to problems involving the simulation and control of the evolution of density matrices in other contexts.

Bio. Claude Le Bris is a civil engineer in chief, HdR from University Paris Dauphine. His applied mathematics works have primarily been devoted to the design and analysis of numerical approaches for Physics and Mechanics. He holds a research position at Ecole des Ponts et Chaussées. He is the scientific leader of the project-team  MATHERIALS at INRIA, the activity of which is focused on multiscale numerical simulation.

S³ seminar : Recursive State Estimation for Nonlinear Stochastic Systems and Application to a Continuous Glucose Monitoring System

Séminaire le 9 Juin 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Alexandros Charalampidis (CentraleSupélec, Rennes)


The talk will start with an introduction to recursive state estimation. It will be presented how the problem can be solved exactly in two important cases (systems with finite state space and linear Gaussian systems). The difficulties associated with nonlinear systems will be explained and the main techniques will be presented (Extended Kalman Filter, Unscented Kalman Filter, Gauss-Hermite Kalman Filter, Particle Filtering, Gaussian Sums). Then the talk will focus on systems that consist of linear dynamical systems interconnected through static nonlinear characteristics. It will be explained that for them, it is possible to avoid integration on the space space, which may be of high order, reducing it to the solution of some linear systems and low-order integration. This way, more accurate calculations can be made. Additionally, a novel quadrature technique, alternative to the Gauss-Hermite quadrature, specially designed for nonlinear filters using norm minimization concepts will be presented. The proposed techniques are applied to an example and it is shown that they can lead to a significant improvement. The final part of the talk will deal with the application of filters to data from a Continuous Glucose Monitoring System (CGMS). The importance of the CGMS to the construction of an artificial pancreas will be explained. It will be shown that, using simple models of the system dynamics, the application of Kalman and Particle Filtering to experimental data from ICU patients leads to an important reduction of the glucose estimation error.

S³ seminar : Inversion de données en traitement du signal et des images : régularisation parcimonieuse et algorithmes de minimisation L0.

Séminaire le 23 Mai 2017, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Charles SOUSSEN, (Centre de Recherche en Automatique de Nancy (CRAN, UMR CNRS 7039), Université de Lorraine)


Dans la première partie de l'exposé, je présenterai différents problèmes inverses auxquels je me suis intéressé ces dernières années et les contextes applicatifs associés : reconstruction d'images en tomographie, analyse d'images biologiques et d'images hyperspectrales en microscopie, problèmes d'inversion de données en spectroscopie optique avec applications biomédicales. Lorsque les données disponibles sont en nombre limité et partiellement informatives sur la quantité à estimer (problèmes inverses mal posés), la prise en compte d’informations a priori sur les inconnues est indispensable, et s’effectue par le biais des techniques de régularisation. Dans la seconde partie de l'exposé, je présenterai plus particulièrement la régularisation parcimonieuse de problèmes inverses, basée sur la minimisation de la "norme" l0. Les algorithmes heuristiques proposés sont conçus pour minimiser des critères mixtes L2-L0 du type

min_x J(x;lambda) = || y - Ax ||_2^2 + lambda || x ||_0.

Ce problème d'optimisation est connu pour être fortement non-convexe et NP-difficile. Les heuristiques proposées (appelées algorithmes "gloutons") sont définies en tant qu'extensions d'Orthogonal Least Squares (OLS). Leur développement est motivé par le très bon comportement empirique d'OLS et de ses versions dérivées lorsque la matrice A est mal conditionnée. Je présenterai deux types d'algorithmes pour minimiser J(x;lambda) à lambda fixé et pour un continuum de valeurs de lambda. Finalement, je présenterai quelques résultats théoriques visant à garantir que les algorithmes gloutons permettent de reconstruire exactement le support d'une représentation parcimonieuse y = Ax*, c'est-à-dire le support du vecteur x*.

Biographie : Charles Soussen est né en France en 1972. Il est diplômé de l'Ecole Nationale Supérieure en Informatique et Mathématiques Appliquées, Grenoble (ENSIMAG) en 1996. Il a obtenu sa thèse en traitement du signal et des images au Laboratoire des Signaux et Systèmes (L2S), Université de Paris-Sud, Orsay, en 2000, et son Habilitation à Diriger des Recherches à l'Université de Lorraine en 2013. Il est actuellement Maître de Conférences à l'Université de Lorraine, et au Centre de Recherche en Automatique de Nancy depuis 2005. Ses thématiques de recherche concernent les problèmes inverses et l'approximation parcimonieuse.

S³ seminar : Deux trous noirs dans une meule de foin : analyse de données pour l'astronomie gravitationnelle

Séminaire le 19 Mai 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Eric Chassande-Mottin, (CNRS, AstroParticule et Cosmologie, Université Paris Diderot)


Le 14 septembre 2015, les deux détecteurs du Laser Interferometer Gravitational-wave Observatory (LIGO) inauguraient une nouvelle ère pour l'astrophysique en observant pour la première fois une onde gravitationnelle issue de la fusion de deux trous noirs faisant chacun trente fois la masse du soleil environ et situés à une distance supérieure à un milliard d'années-lumière. On donnera une vue d'ensemble de cette découverte majeure en insistant sur les méthodes d'analyse de données utilisées pour sortir le signal du bruit complexe rencontré dans ces expériences.

Coded Caching in Wireless Networks

Séminaire le 19 Mai 2017, 09h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Meixia Tao


The global mobile data traffic has been shifting from voice and messages to rich content distributions, such as video streaming and application downloads. These contents are typically produced ahead of transmission and can be requested by multiple users though at possibly different times. By prefetching popular contents during off-peak times at the edge of wireless networks, such as small base stations, helper nodes, and user devices, wireless caching can alleviate peak-time network congestion and reduce user access latency. A fundamental question is what and how much gain can be leveraged by caching. In this talk, we shall investigate the gain of caching in two types of wireless networks. One is a general wireless interference network with arbitrary number of transmitters and arbitrary number of receives and with caches equipped at all the nodes. An information-theoretic study in terms of the storage-latency tradeoff will be presented. The other is a large-scale small-cell network where each small base station is equipped with a cache. We apply stochastic geometry to model, analyze, and optimize coded caching with performances characterized by average fractional offloaded traffic and average ergodic rate. Our study reveals several design insights of caching in practical wireless networks.

Bio: Meixia Tao received the B.S. degree from Fudan University, Shanghai, China, in 1999, and the Ph.D. degree from Hong Kong University of Science and Technology in 2003. She is currently a Professor with the Department of Electronic Engineering, Shanghai Jiao Tong University, China. Prior to that, she was a Member of Professional Staff at Hong Kong Applied Science and Technology Research Institute during 2003-2004, and a Teaching Fellow then an Assistant Professor at the Department of Electrical and Computer Engineering, National University of Singapore from 2004 to 2007. Her current research interests include content-centric wireless networks, wireless caching and multicasting, resource allocation, and interference coordination.

Dr. Tao is currently serving as a member of the Executive Editorial Committee of the IEEE Transactions on Wireless Communications and an Editor for the IEEE Transactions on Communications. Dr. Tao is the recipient of the IEEE Heinrich Hertz Award for Best Communications Letters in 2013 and the IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award in 2009. She also receives the best paper awards from IEEE/CIC ICCC 2015 and IEEE WCSP 2012.

Semantically-Secured Message-Key Trade-off over Wiretap Channels with Random Parameters

Séminaire le 4 Mai 2017, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Alexander Bunin, Faculty of Electrical Engineering at the Technion-Israel Institute of Technology, Israel.


Modern communication systems usually present an architectural separation between error correction and data encryption. The former is typically realized at the physical layer by transforming the noisy communication channel into a reliable "bit pipe". The data encryption is implemented on top of that by applying cryptographic principles.

Physical layer security (PLS) rooted in information-theoretic principles, is an alternative approach to provably secure communication. This approach dates back to Wyner's celebrated 1975 paper on the wiretap channel (WTC). By harnessing randomness from the noisy communication channel and combining it with proper physical layer coding, PLS guarantees protection against computationally-unlimited eavesdroppers with no requirement that the legitimate parties share a secret key (SK) in advance. The eavesdroppers computational abilities are of no consequence here since the signal he/she observes from the channel carries only negligible information about the secret data.

Two fundamental questions in PLS are those of the best achievable transmission rate of a secret message (SM) over a noisy channel, and the highest attainable SK rate that distributed parties can agree upon. Our work studies the trade-off between SM and SK rates simultaneously achievable over a state-dependent wiretap channel WTC with non-causal channel state information (CSI) at the encoder. This model subsumes all other instances of CSI availability as special cases, and calls for an efficient utilization of the state sequence both for reliability and security purposes. We derive an inner bound on the SM-SK capacity region based on a novel superposition coding scheme. Our inner bound improves upon the previously best known SM-SK trade-off result by Prabhakaran et al., and to the best of our knowledge, upon all other existing lower bounds for either SM or SK for this setup. The results are derived under the strict semantic-security metric that requires negligible information leakage for all message-key distributions. The achievability proof uses the strong soft-covering lemma for superposition codes.
The talk is based on joint work with: Z. Goldfeld and H. H. Permuter (Ben-Gurion University of the Negev, Israel), S. Shamai (Technion - Israel Institute of Technology), P. W. Cuff (Princeton University) and P. Piantanida (CentralSupelec).
The work of A. Bunin and S. Shamai has been supported by the European Union's Horizon 2020 Research And Innovation Programme, grant agreement no. 694630.

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