Publications

2017

• Trends in Social Network Analysis - Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment
  
  • Missaoui Rokia
  • Abdessalem Talel
  • Latapy Mathieu
  , 2017, pp.255. <p>The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, stochastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.</p> <p> </p> (10.1007/978-3-319-53420-6)
  DOI : 10.1007/978-3-319-53420-6
• La fabrique des données brutes. Le travail en coulisses de l'open data
  
  • Denis Jérôme
  • Goëta Samuel
  , 2017. Depuis quelques années, les initiatives d’open data se sont multipliées à travers le monde. Présentées jusque dans la presse grand public comme une ressource inexploitée, le « pétrole » sur lequel le monde serait assis, les données publiques sont devenues objet de toutes les attentions et leur ouverture porteuse de toutes les promesses, à la fois terreau d’un renouveau démocratique et moteur d’une innovation distribuée. Comme dans les sciences, qui ont connu un mouvement de focalisation similaire sur les données et leur partage, l’injonction à l’ouverture opère une certaine mise en invisibilité. Le vocabulaire de la « libération », de la « transparence » et plus encore celui de la « donnée brute » efface toute trace des conditions de production des données, des contextes de leurs usages initiaux et pose leur universalité comme une évidence. Ce chapitre explore les coulisses de l’open data afin de retrouver les traces de cette production et d’en comprendre les spécificités. À partir d’une série d’entretiens ethnographiques dans diverses institutions, il décrit la fabrique des données brutes, dont l’ouverture ne se résume jamais à une mise à disponibilité immédiate, évidente et universelle. Il montre que trois aspects sont particulièrement sensibles dans le processus d’ouverture : l’identification, l'extraction et la « brutification » des données. Ces trois séries d’opérations donnent à voir l’épaisseur sociotechnique des données brutes dont la production mêle dimensions organisationnelles, politiques et techniques.
• CLEAR: Covariant LEAst-Square Refitting with Applications to Image Restoration
  
  • Deledalle Charles-Alban
  • Papadakis Nicolas
  • Salmon Joseph
  • Vaiter Samuel
  SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2017, 10 (1), pp.243-284. In this paper, we propose a new framework to remove parts of the systematic errors affecting popular restoration algorithms, with a special focus for image processing tasks. Generalizing ideas that emerged for $\ell_1$ regularization, we develop an approach re-fitting the results of standard methods towards the input data. Total variation regularizations and non-local means are special cases of interest. We identify important covariant information that should be preserved by the re-fitting method, and emphasize the importance of preserving the Jacobian (w.r.t. the observed signal) of the original estimator. Then, we provide an approach that has a ``twicing'' flavor and allows re-fitting the restored signal by adding back a local affine transformation of the residual term. We illustrate the benefits of our method on numerical simulations for image restoration tasks. (10.1137/16M1080318)
  DOI : 10.1137/16M1080318
• Closed-form expressions of the eigen decomposition of 2 x 2 and 3 x 3 Hermitian matrices
  
  • Deledalle Charles-Alban
  • Denis Loic
  • Tabti Sonia
  • Tupin Florence
  , 2017. The eigen decomposition of covariance matrices is at the core of many data analysis techniques. The study of 2-components or 3-components vector fields typically requires computing numerous eigen decompositions of 2 x 2 or 3 x 3 matrices. This is, for example, the case in the analysis of interferometric or polarimetric SAR images, see MuLoG algorithm (https://hal.archives-ouvertes.fr/hal-01388858). The closed-form expression of eigen-values and eigenvectors then provides a way to derive faster data processing algorithms. This note gives these expressions in the general case (special cases where some coefficients are zero, or the eigenvalues are not separated may not be covered and then require either to introduce a small perturbation of the initial matrix or to derive other expressions).
• Parameter Sensitivity Analysis of the Energy/Frequency Convexity Rule for Nanometer-scale Application Processors
  
  • de Vogeleer Karel
  • Memmi Gerard
  • Jouvelot Pierre
  Sustainable Computing : Informatics and Systems, Elsevier, 2017, 15, pp.16-27. Both theoretical and experimental evidence are presented in this work in order to validate the existence of an Energy/Frequency Convexity Rule, which relates energy consumption and microprocessor frequency for nanometer-scale microprocessors. Data gathered during several month-long experimental acquisition campaigns, supported by several independent publications, suggest that energy consumed is indeed depending on the microprocessor's clock frequency, and, more interestingly, the curve exhibits a clear minimum over the processor's frequency range. An analytical model for this behavior is presented and motivated, which fits well with the experimental data. A parameter sensitivity analysis shows how parameters affect the energy minimum in the clock frequency space. The conditions are discussed under which this convexity rule can be exploited, and when other methods are more effective, with the aim of improving the computer system's energy management efficiency. We show that the power requirements of the computer system, besides the microprocessor, and the overhead affect the location of the energy minimum the most. The sensitivity analysis of the Energy/Frequency Convexity Rule puts forward a number of simple guidelines especially for by low-power systems, such as battery-powered and embedded systems, and less likely by high-performance computer systems. (10.1016/j.suscom.2017.05.001)
  DOI : 10.1016/j.suscom.2017.05.001
• FDOPA Patterns in Adrenal Glands
  
  • Moreau Aurélie
  • Giraudet Anne Laure
  • Kryza David
  • Borson-Chazot Françoise
  • Bournaud-Salinas Claire
  • Mognetti Thomas
  • Lifante Jean-Christophe
  • Combemale Patrick
  • Giammarile Francesco
  • Houzard Claire
  Clinical Nuclear Medicine, Lippincott, Williams & Wilkins, 2017, 42 (5), pp.379-382. (10.1097/RLU.0000000000001636)
  DOI : 10.1097/RLU.0000000000001636
• Convergence to multi-resource fairness under end-to-end window control
  
  • Bonald Thomas
  • Roberts James
  • Vitale Christian
  , 2017. The paper relates to multi-resource sharing between flows with heterogeneous requirements as arises in networks with wireless links or software routers implementing network function virtualization. Bottleneck max fairness (BMF) is a sharing objective in this context with good performance. The paper shows that BMF results when local fairness is imposed at each resource while flow rates are controlled by an end-to-end window. We analytically prove convergence to BMF under a fluid model when flows share a network limited to 2 resources while numerical results confirm BMF convergence for larger networks. Simulation results illustrate the impact of packetized transmission.
• Using modular extension to provably protect Edwards curves against fault attacks
  
  • Dugardin Margaux
  • Guilley Sylvain
  • Moreau Martin
  • Najm Zakaria
  • Rauzy Pablo
  Journal of Cryptographic Engineering, Springer, 2017, vol. 7, nb. 4.
• Towards the Generation of Expressive Co-Speech Gestures
  
  • Ravenet Brian
  • Clavel Chloé
  • Pelachaud Catherine I
  , 2017.
• Acoustic Features for Environmental Sound Analysis
  
  • Serizel Romain
  • Bisot Victor
  • Essid Slim
  • Richard Gael
  , 2017, pp.71-101. Most of the time it is nearly impossible to differentiate between particular type of sound events from a waveform only. Therefore, frequency domain and time-frequency domain representations have been used for years providing representations of the sound signals that are more inline with the human perception. However, these representations are usually too generic and often fail to describe specific content that is present in a sound recording. A lot of work have been devoted to design features that could allow extracting such specific information leading to a wide variety of hand-crafted features. During the past years, owing to the increasing availability of medium scale and large scale sound datasets, an alternative approach to feature extraction has become popular, the so-called feature learning. Finally, processing the amount of data that is at hand nowadays can quickly become overwhelming. It is therefore of paramount importance to be able to reduce the size of the dataset in the feature space. The general processing chain to convert an sound signal to a feature vector that can be efficiently exploited by a classifier and the relation to features used for speech and music processing are described is this chapter. (10.1007/978-3-319-63450-0_4)
  DOI : 10.1007/978-3-319-63450-0_4
• 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.
• 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
• Dispositif échantillonneur- bloqueur de signal électrique
  
  • Meyer A.
  • Louis B.
  • Corbière Rémi
  • Petit V.
  • Desgreys Patricia
  • Petit H.
  , 2017.
• 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.
• 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
• 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.
• 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.
• 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.
• 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
• Signal and quantum noise in optical communications and in cryptography
  
  • Gallion Philippe
  • Mendieta F J
  • Jiang Shifeng
  , 2017.