Publications

2017

• Balanced Fair Resource Sharing in Computer Clusters
  
  • Bonald Thomas
  • Comte Céline
  Performance Evaluation, Elsevier, 2017. We represent a computer cluster as a multi-server queue with some arbitrary graph of compatibilities between jobs and servers. Each server processes its jobs sequentially in FCFS order. The service rate of a job at any given time is the sum of the service rates of all servers processing this job. We show that the corresponding queue is quasi-reversible and use this property to design a scheduling algorithm achieving balanced fair sharing of the computing resources. (10.1016/j.peva.2017.08.006)
  DOI : 10.1016/j.peva.2017.08.006
• Towards a framework for the levels and aspects of selfaware computing systems
  
  • Lewis Peter
  • Bellman Kirstie
  • Landauer Chris
  • Esterle Lukas
  • Glette Kyrre
  • Diaconescu Ada
  • Giese Holger
  , 2017, pp.51-85.
• Goal-oriented Holonic Systems
  
  • Diaconescu Ada
  , 2017, pp.209-258.
• Repenser les médiations. Analyse des manières de faire découvrir et apprécier les œuvres et pratiques culturelles, de la production à la réception
  
  • Bonnéry Stéphane
  • Coavoux Samuel
  • Deslyper Rémi
  • Eloy Florence
  • Francois Sébastien
  • Giraud Frédérique
  • Legon Tomas
  • Mille Muriel
  , 2017.
• Multiview approaches to event detection and scene analysis
  
  • Essid Slim
  • Parekh Sanjeel
  • Duong Ngoc Q. K.
  • Serizel Romain
  • Ozerov Alexey
  • Antonacci Fabio
  • Sarti Augusto
  , 2017, pp.243-276. This chapter addresses sound scene and event classification in multiview settings, that is, settings where the observations are obtained from multiple sensors, each sensor contributing a particular view of the data (e.g., audio microphones, video cameras, etc.). We briefly introduce some of the techniques that can be exploited to effectively combine the data conveyed by the different views under analysis for a better interpretation. We first provide a high-level presentation of generic methods that are particularly relevant in the context of multiview and multimodal sound scene analysis. Then, we more specifically present a selection of techniques used for audiovisual event detection and microphone array-based scene analysis. (10.1007/978-3-319-63450-0_9)
  DOI : 10.1007/978-3-319-63450-0_9
• On Stochastic Proximal Gradient Algorithms
  
  • Atchadé Y.
  • Fort Gersende
  • Moulines Eric
  Journal of Machine Learning Research, Microtome Publishing, 2017.
• Dispositif échantillonneur- bloqueur de signal électrique
  
  • Meyer A.
  • Louis B.
  • Corbière Rémi
  • Petit V.
  • Desgreys Patricia
  • Petit H.
  , 2017.
• On metric convexity, the discrete Hahn-Banach theorem, separating systems and sets of points forming only acute angles
  
  • Randriambololona Hugues
  Int. J. of Information and Coding Theory, 2017, 4 (2/3), pp.159-169.
• A top-down engineering curriculum and application to a French "grande école
  
  • Chinchilla Raphael
  • Rodriguez G.
  IEEE Transactions on Education, Institute of Electrical and Electronics Engineers, 2017.
• Topological relations between bipolar fuzzy sets based on mathematical morphology
  
  • Bloch Isabelle
  , 2017, LNCS 10225, pp.40-51. In many domains of information processing, both vagueness, or imprecision, and bipolarity, encompassing positive and negative parts of information, are core features of the information to be modeled and processed. This led to the development of the concept of bipolar fuzzy sets, and of associated models and tools. Here we propose to extend these tools by defining set theoretical and topological relations between bipolar fuzzy sets, including intersection, inclusion, adjacency and RCC relations widely used in mereotopology, based on bipolar connectives and on mathematical morphology operators.
• A new method based on template registration and deformable models for pelvic bones semi-automatic segmentation in pediatric MRI
  
  • Virzi Alessio
  • Marret Jean-Baptiste
  • Muller Cécile
  • Berteloot Laureline
  • Boddaert Nathalie
  • Sarnacki Sabine
  • Bloch Isabelle
  , 2017, pp.323-326. In this paper we address the problem of bone segmentation in MRI images of children, in the region of the pelvis. To cope with the complex structure of the bones in this region and their changing topology during growth, we propose a method relying on 3D bone templates. These models are built from 3D CT images. For a given MRI volume, the closest template is chosen and registered on the MRI data. This leads to an initial segmentation which is then refined using a deformable model approach, where the regularization parameters depend on the local curvature, and the landmarks used during the registration are fixed anchors during the deformation. This approach was successfully applied to 15 MRI volumes of children between 1 and 18 years old, with an average accuracy in terms of medium distance of M D = 1.17 ± 0.29 mm and Dice Index of DC = 0.81 ± 0.04.
• Brain MRI Segmentation using Fully Convolutional Network and Transfer Learning
  
  • Xu Yongchao
  • Géraud Thierry
  • Puybareau Elodie
  • Bloch Isabelle
  , 2017.
• Exploring structure for long-term tracking of multiple objects in sports videos
  
  • Morimitsu Henrique
  • Bloch Isabelle
  • Cesar R. M.
  Computer Vision and Image Understanding, Elsevier, 2017, 159, pp.89-104. In this paper we propose a novel approach for exploring structural relations to track multiple objects that may undergo long-term occlusion and abrupt motion. We use a model-free approach that relies only on annotations given in the first frame of the video to track all the objects online, i.e. without knowledge from future frames. We initialize a probabilistic Attributed Relational Graph (ARG) from the first frame, which is incrementally updated along the video. Instead of using structural information only to evaluate the scene, the proposed approach considers it to generate new tracking hypotheses. In this way, our method is capable of generating relevant object candidates that are used to improve or recover the track of lost objects. The proposed method is evaluated on several videos of table tennis matches and on the ACASVA dataset. The results show that our approach is very robust, flexible and able to outperform other state-of-the-art methods in sports videos that present structural patterns.
• Application cases of secret key generation in communication nodes and terminals
  
  • Sibille Alain
  • Delaveau François
  • Kameni Ngassa Christiane L.
  • Molière Renaud
  • Mazloum Taghrid
  • Kotelba Adrian
  • Suomalainen Jani
  • Boumard Sandrine
  • Shapira Nir
  , 2017. The main objective of this chapter is to study explicit key extraction techniques and algorithms for the security of radio communication. After some recalls on the main processing steps (Figure 19.1(a)) and on theoretical results relevant to the radio wiretap model (Figure 19.1(b)), we detail recent experimental results on randomness properties of real field radio channels. Furthermore, we detail a practical implantation of secret key generation (SKG) schemes, based on the Channel Quantization Alternate (CQA) algorithm helped with channel decorrelation techniques, into modern public networks such as WiFi and radio-cells of fourth generation (LTE, long-term evolution). Finally, through realistic simulations and real field experiments of radio links, we analyze the security performance of the implemented SKG schemes, and highlight their significant practical results and perspectives for future implantations into existing and next-generation radio standards.
• A model of perceived dynamic range for HDR images
  
  • Hulusic Vedad
  • Debattista Kurt
  • Valenzise Giuseppe
  • Dufaux Frédéric
  Signal Processing: Image Communication, Elsevier, 2017, 51, pp.26 - 39. For High Dynamic Range (HDR) content, the dynamic range of an image is an important characteristic in algorithm design and validation, analysis of aesthetic attributes and content selection. Traditionally, it has been computed as the ratio between the maximum and minimum pixel luminance, a purely objective measure; however, the human visual system's perception of dynamic range is more complex and has been largely neglected in the literature. In this paper, a new methodology for measuring perceived dynamic range (PDR) of chromatic and achromatic HDR images is proposed. PDR can benefit HDR in a number of ways: for evaluating inverse tone mapping operators and HDR compression methods; aesthetically; or as a parameter for content selection in perceptual studies. A subjective study was conducted on a data set of 36 chromatic and achromatic HDR images. Results showed a strong agreement across participants' allocated scores. In addition, a high correlation between ratings of the chromatic and achromatic stimuli was found. Based on the results from a pilot study, five objective measures (pixel-based dynamic range, image key, area of bright regions, contrast and colorfulness) were selected as candidates for a PDR predictor model; two of which have been found to be significant contributors to the model. Our analyses show that this model performs better than individual metrics for both achromatic and chromatic stimuli. (10.1016/j.image.2016.11.005)
  DOI : 10.1016/j.image.2016.11.005
• Signal and quantum noise in optical communications and in cryptography
  
  • Gallion Philippe
  • Mendieta F J
  • Jiang Shifeng
  , 2017.
• Safe and Secure Support for Public Safety Networks
  
  • Apvrille Ludovic
  • Li Letitia W.
  , 2017, pp.185 - 210. <p>As explained by Tanzi et al. in the first volume of this book, communicating and autonomous devices will surely have a role to play in the future Public Safety Networks. The “communicating” feature comes from the fact that the information should be delivered in a fast way to rescuers. The “autonomous” characteristic comes from the fact that rescuers should not have to concern themselves about these objects: they should perform their mission autonomously so as not to delay the intervention of the rescuers, but rather to assist them efficiently and reliably.</p> (10.1016/B978-1-78548-053-9.50009-3)
  DOI : 10.1016/B978-1-78548-053-9.50009-3
• Optimize Wireless Networks for Energy Saving by Distributed Computation of Čech Complex
  
  • Le Ngoc-Khuyen
  • Vergne Anais
  • Martins Philippe
  • Decreusefond Laurent
  , 2017. In this paper, we introduce a distributed algorithm to compute the \v{C}ech complex. This algorithm is aimed at solving the coverage problems in self organized wireless networks. The complexity to compute the minimal \v{C}ech complex that gives information about coverage and connectivity of the network is $\mathcal{O}(n^2)$, where $n$ is the average number of neighbors of each cell. An application based on the distributed computation of the \v{C}ech complex, which is aimed at optimizing the wireless network for energy saving, is also proposed. This application also has polynomial complexity. The performance of the proposed algorithm and its application are evaluated. The simulation results show that the distributed computation of the \v{C}ech complex provides a consistent outcome with the one obtained by the centralized computation that is introduced in [6], while requires a much shorter calculation time. The optimized coverage saves 65\% of the total transmission power, while also keeps the maximal coverage for the network.
• Optimal scaling of the Random Walk Metropolis algorithm under Lp mean differentiability
  
  • Durmus Alain
  • Le Corff Sylvain
  • Moulines Éric
  • Roberts Gareth O. O.
  Journal of Applied Probability, Cambridge University press, 2017, 54 (4), pp.1233 -1260. This paper considers the optimal scaling problem for high-dimensional random walk Metropolis algorithms for densities which are differentiable in Lp mean but which may be irregular at some points (like the Laplace density for example) and/or are supported on an interval. Our main result is the weak convergence of the Markov chain (appropriately rescaled in time and space) to a Langevin diffusion process as the dimension d goes to infinity. Because the log-density might be non-differentiable, the limiting diffusion could be singular. The scaling limit is established under assumptions which are much weaker than the one used in the original derivation of [6]. This result has important practical implications for the use of random walk Metropolis algorithms in Bayesian frameworks based on sparsity inducing priors. (10.1017/jpr.2017.61)
  DOI : 10.1017/jpr.2017.61
• More Results on the Complexity of Domination Problems in Graphs
  
  • Hudry Olivier
  • Lobstein Antoine
  International Journal of Information and Coding Theory, Inderscience, 2017, 4 (2/3), pp.129-144. Given a graph G = (V, E) and an integer r &ge; 1, we call 'r-dominating code' any subset C of V such that every vertex in V is at distance at most r from at least one vertex in C. We investigate and locate in the complexity classes of the polynomial hierarchy, several problems linked with domination in graphs, such as, given r and G, the existence of, or search for, optimal r-dominating codes in G, or optimal r-dominating codes in G containing a subset of vertices X &sub; V . (10.1504/ijicot.2017.083829)
  DOI : 10.1504/ijicot.2017.083829
• Synchronization in MPEG-4 Systems
  
  • Le Feuvre J.
  • Concolato Cyril
  , 2017, 18, pp.451-473. (10.1007/978-3-319-65840-7)
  DOI : 10.1007/978-3-319-65840-7
• A Bayesian Hyperprior Approach for Joint Image Denoising and Interpolation, with an Application to HDR Imaging
  
  • Aguerrebere Cecilia
  • Almansa Andrés
  • Delon Julie
  • Gousseau Yann
  • Musé Pablo
  IEEE Transactions on Computational Imaging, IEEE, 2017. Recently, impressive denoising results have been achieved by Bayesian approaches which assume Gaussian models for the image patches. This improvement in performance can be attributed to the use of per-patch models. Unfortunately such an approach is particularly unstable for most inverse problems beyond denoising. In this work, we propose the use of a hyperprior to model image patches, in order to stabilize the estimation procedure. There are two main advantages to the proposed restoration scheme: Firstly it is adapted to diagonal degradation matrices, and in particular to missing data problems (e.g. inpainting of missing pixels or zooming). Secondly it can deal with signal dependent noise models, particularly suited to digital cameras. As such, the scheme is especially adapted to computational photography. In order to illustrate this point, we provide an application to high dynamic range imaging from a single image taken with a modified sensor, which shows the effectiveness of the proposed scheme. (10.1109/TCI.2017.2704439)
  DOI : 10.1109/TCI.2017.2704439
• Behavioural semantics for asynchronous components
  
  • Ameur-Boulifa Rabéa
  • Henrio Ludovic
  • Kulankhina Oleksandra
  • Madelaine Eric
  • Savu Alexandra
  Journal of Logical and Algebraic Methods in Programming, Elsevier, 2017, 89, pp.1 - 40. Software components are a valuable programming abstraction that enables a compositional design of complex applications. In distributed systems, components can also be used to provide an abstraction of locations: each component is a unit of deployment that can be placed on a different machine. In this article, we consider this kind of distributed components that are additionally loosely coupled and communicate by asynchronous invocations. Components also provide a convenient abstraction for verifying the correct behaviour of systems: they provide structuring entities easing the correctness verification. This article provides a formal background for the generation of behavioural semantics for asynchronous components. It expresses the semantics of hierarchical distributed components communicating asynchronously by requests, futures, and replies; this semantics is provided using the pNet intermediate language. This article both demonstrates the expressiveness of the pNet model and formally specifies the complete process of the generation of a behavioural model for a distributed component system. The purpose of our be-havioural semantics is to allow for verification both by finite instantiation and model-checking, and by techniques for infinite systems. (10.1016/j.jlamp.2017.02.003)
  DOI : 10.1016/j.jlamp.2017.02.003
• MCMC design-based non-parametric regression for rare event. Application to nested risk computation.
  
  • Fort Gersende
  • Gobet Emmanuel
  • Moulines Éric
  Monte Carlo Methods and Applications, De Gruyter, 2017.
• Fast and privacy preserving distributed low-rank regression
  
  • Wai Hoi-To
  • Lafond Jean
  • Scaglione Anna
  • Moulines Éric
  , 2017.