Publications

2017

• Beat gesture prediction using prosodic features
  
  • Jain Varun
  • Clavel Chloé
  • Pelachaud Catherine
  , 2017. In this work we present a machine learning approach to gesture prediction using prosodic features. We use conditional random fields to predict the presence of beat gestures using the following prosodic features: pitch, pitch-derivatives, intensity and absence or presence of syllable nuclei. These features are calculated over overlapping sliding windows big enough to average out the high frequency variations associated with pitch and intensity at the syllable level. We found that the results improve remarkably when the classification is treated as a multi-class problem as opposed to a binary problem with the two classes: presence and absence of gesture.
• Asymptotic properties of quasi-maximum likelihood estimators in observation-driven time series models
  
  • Douc Randal
  • Fokianos Konstantinos
  • Moulines Éric
  Electronic Journal of Statistics, Shaker Heights, OH : Institute of Mathematical Statistics, 2017, 11 (2), pp.2707 - 2740. We study a general class of quasi-maximum likelihood estimators for observation-driven time series models. Our main focus is on models related to the exponential family of distributions like Poisson based models for count time series or duration models. However, the proposed approach is more general and covers a variety of time series models including the ordinary GARCH model which has been studied extensively in the literature. We provide general conditions under which quasi-maximum likelihood estimators can be analyzed for this class of time series models and we prove that these estimators are consistent and asymptotically normally distributed regardless of the true data generating process. We illustrate our results using classical examples of quasi-maximum likelihood estimation including standard GARCH models, duration models, Poisson type autoregressions and ARMA models with GARCH errors. Our contribution unifies the existing theory and gives conditions for proving consistency and asymptotic normality in a variety of situations (10.1214/17-EJS1299)
  DOI : 10.1214/17-EJS1299
• Laser ultrarapide à base d'une fibe active fortement dispersive
  
  • Hideur Ammar
  • Tang Ming
  • Lesparre F.
  • Wang H.
  • Qian K.
  • Lecaplain C.
  • Jossent M.
  • Oudar Jean-Louis
  • Jaouën Yves
  • Gabet Renaud
  • Gaponov D.
  • Likhachev M.
  , 2017.
• Oscillateurs à boîtes quantiques à très faible largeur de raie pour les systèmes optiques cohérents
  
  • Duan Jianan
  • Huang Heming
  • Schires Kevin
  • Poole Philip
  • Grillot Frédéric
  , 2017.
• Double Hierarchies for Efficient Sampling in Monte Carlo Rendering
  
  • Bus Norbert
  • Boubekeur Tamy
  , 2017.
• Bounding Proxies for Shape Approximation
  
  • Calderon Stéphane
  • Boubekeur Tamy
  ACM Transactions on Graphics, Association for Computing Machinery, 2017, 36 (5), pp.57.1-57.13. <p>Many computer graphics applications use simpler yet faithful approximations of complex shapes to conduct reliably part of their computations. Some tasks, such as physical simulation, collision detection, occlusion queries or free-form deformation, require the simpler proxy to strictly enclose the input shape. While there are algorithms that can output such bounding proxies on simple input shapes, most of them fail at generating a proper coarse approximant on real-world complex shapes, which may contain multiple components and have a high genus. We advocate that, before reducing the number of primitives to describe a shape, one needs to regularize it while maintaining the strict enclosing property, to avoid any geometric aliasing that makes the decimation unreliable. Depending on the scale of the desired approximation, the topology of the shape itself may indeed have to be first simplified, to let the subsequent geometric optimization be free from topological locks.</p> <p> </p> <p>We propose a new bounding shape approximation algorithm which takes as input an arbitrary surface mesh, with potentially complex multi-component structures, and generates automatically a bounding proxy which is tightened on the input and can match even the coarsest levels of approximation. To sustain the nonlinear approximation process that may eventually abstract both geometry and topology, we propose to use an intermediate regularized representation in the form of a shape closing, computed in real time using a new fast morphological framework designed for efficient parallel execution. Once the desired level of approximation is reached in the shape closing, a coarse, tight and bounding polygonization of the proxy geometry is extracted using an adaptive meshing scheme. Our underlying representation is both geometry- and topology-adaptive and can be optionally controlled accurately by a user, through sizing and orientation fields, yielding an intuitive brush metaphor within an interactive proxy design environment. We provide extensive experiments on various kinds of input meshes and illustrate the potential applications of our method in scenarios that benefit greatly from coarse, tight bounding substitutes to the actual high resolution geometry of the original 3D model, including freeform deformation, physical simulation and level of detail generation for rendering.</p>
• Proxy Clouds for RGB-D Stream Processing: An Insight
  
  • Kaiser Adrien
  • Ybanez Zepeda Jose Alonso
  • Boubekeur Tamy
  , 2017.
• Combined polarization- and mode-dependant loss effects on few-mode fibers systems
  
  • Amhoud El Mehdi
  • Rekaya-Ben Othman Ghaya
  • Jaouën Yves
  , 2017, pp.paper SpM4F3.
• A complexity based approach for solving Hofstadter's analogies
  
  • Murena Pierre-Alexandre
  • Dessalles Jean-Louis
  • Cornuéjols Antoine
  , 2017, pp.53-62. Analogical reasoning is still a difficult task for machines. In this paper, we consider the problem of analogical reasoning and assume that the relevance of a solution can be measured by the complexity of the analogy. This hypothesis is tested in a basic alphanumeric micro-world.
• A stochastic approach for packet dropping attacks detection in mobile Ad hoc networks
  
  • Rmayti Mohammad
  • Khatoun Rida
  • Begriche Youcef
  • Khoukhi Lyes
  • Gaïti Dominique
  Computer Networks, Elsevier, 2017, 121, pp.53-64. (10.1016/j.comnet.2017.04.027)
  DOI : 10.1016/j.comnet.2017.04.027
• Caractérisation de la transition 3F4 – 3H6 dans les fibres silice dopées Thulium et simulation d’un amplificateur 2μm
  
  • Romano Clément
  • Tench Robert
  • Delavaux Jean-Marc
  , 2017, pp.papier #128.
• Stochastic Collision Attack
  
  • Bruneau Nicolas
  • Carlet Claude
  • Guilley Sylvain
  • Heuser Annelie
  • Prouff Emmanuel
  • Rioul Olivier
  IEEE Transactions on Information Forensics and Security, Institute of Electrical and Electronics Engineers, 2017, 12 (9), pp.2090 - 2104. On the one hand, collision attacks have been introduced in the context of side-channel analysis for attackers who exploit repeated code with the same data without having any knowledge of the leakage model. On the other hand, stochastic attacks have been introduced to recover leakage models of internally processed intermediate secret variables. Both techniques have shown advantages and intrinsic limitations. Most collision attacks, for instance, fail in exploiting all the leakages (e.g., only a subset of matching samples are analyzed), whereas stochastic attacks cannot involve linear regression with the full basis (while the latter basis is the most informative one). In this paper, we present an innovative attacking approach, which combines the flavors of stochastic and collision attacks. Importantly, our attack is derived from the optimal distinguisher, which maximizes the success rate when the model is known. Notably, we develop an original closed-form expression, which shows many benefits by using the full algebraic description of the leakage model. Using simulated data, we show in the unprotected case that, for low noise, the stochastic collision attack is superior to the state of the art, whereas asymptotically and thus, for higher noise, it becomes equivalent to the correlation-enhanced collision attack. Our so-called stochastic collision attack is extended to the scenario where the implementation is protected by masking. In this case, our new stochastic collision attack is more efficient in all scenarios and, remarkably, tends to the optimal distinguisher. We confirm the practicability of the stochastic collision attack thanks to experiments against a public data set (DPA contest v4). Furthermore, we derive the stochastic collision attack in case of zero-offset leakage that occurs in protected hardware implementations and use simulated data for comparison. Eventually, we underline the capability of the new distinguisher to improve its efficiency when the attack multiplicity increases. (10.1109/TIFS.2017.2697401)
  DOI : 10.1109/TIFS.2017.2697401
• Ultra-high resolution programmable arbitrary optical filter: design and applications
  
  • Wei Wei
  • Jaouën Yves
  • Yi L. L.
  • Fresnel Schadrac
  • Besnard Pascal
  , 2017.
• Towards WDM Slot switching for aggregation access and metropolitan applications: the ANR N-GREEN project
  
  • Ware Cédric
  • Chiaroni Dominique
  , 2017 (Mo.B2.4).
• Pre-coded NRZ and Electrical Duo-Binary Transmission in C and O-band at Data Bit Rate up to 25Gbit/s
  
  • Konopacki Justine
  • Le Guyader Bertrand
  • Genay Naveena
  • Anet Neto Luiz
  • Chanclou Philippe
  • Erasme Didier
  , 2017, TU-P7.
• Interactional Justice for Sustainable Management of Common-Pool Resources
  
  • Pitt Jeremy
  • Diaconescu Ada
  , 2017.
• Unsupervised detection of thin water surfaces in SWOT images based on segment detection and connection
  
  • Lobry Sylvain
  • Tupin Florence
  • Fjortoft Roger
  , 2017, pp.3720-3723. The objective of the Surface Water and Ocean Topography (SWOT) mission is to regularly monitor the height of the earth’s water surfaces. One of the challenges toward obtaining global measurements of these surfaces is to detect small water areas. In this article we introduce a method for the detection of thin water surfaces, such as rivers, in SWOT images. It combines a low-level step (segment detection) with a high-level regularization of these features. The method is then tested on a simulated SWOT image.
• Software-defined microwave photonic filter with high reconfigurable resoluton
  
  • Yi L. L.
  • Wei Wei
  • Jaouën Yves
  • Hu W.
  , 2017, pp.Session 14, Optical fibers and fabrics.
• SUPPRESSION DU BEAM STEERING DANS UN LASER À CASCADES QUANTIQUES SOUMIS À UNE CONTRE-RÉACTION OPTIQUE EXTERNE
  
  • Spitz Olivier
  • Jumpertz Louise
  • Ferre Simon
  • Carras Mathieu
  • Grillot Frederic
  , 2017. Les lasers à cascades quantiques sont des sources semiconductrices exploitant les transitions inter-sous-bandes au sein de la bande de conduction. Pour les applications de forte puissance, la qualité du faisceau en champ proche est altérée, notamment par le beam steering. Dans cet article, nous montrons que le beam steering peut être efficacement supprimé tout en conservant une bonne qualité de faisceau en champ proche grâce à l'application d'une contre-réaction optique externe.
• COMPARISON BETWEEN PIXEL AND REGION BASED SITS ANALYSIS APPROACHES
  
  • Réjichi S.
  • Chaabane F.
  • Tupin Florence
  , 2017.
• Cost-constrained Viterbi Algorithm for Resource Allocation in Solar Base Stations
  
  • Tran Viet Hung
  • Coupechoux Marceau
  IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers, 2017, 16 (7), pp.4166 - 4180. Solar energy is currently a popular renewable resource, yet limited daily. In green cellular networks, multiple constraints optimization (MCO) problems arise naturally. For example, a typical objective is to control the power transmission of hybrid base stations (connected to both solar panels and electrical grid) in order to maximize user's average throughput, under the constraints of consumed grid energy and user's blocking rate. However, such problems have been generally proved to be NP-hard. In this paper, we formulate this generic MCO problem as a quantized Markovian cost-reward model, with no assumption on input data. We then propose a novel algorithm, namely Cost-constrained Viterbi Algorithm, which recursively returns the optimal policy with linear computational complexity for this model. As an application, we provide engineering rules for the design of hybrid base stations through extensive simulations. In comparison with brute force method for a simple scenario, we find that our algorithm does achieve the constrained optimal policy.
• Formal Methods for Safe Design and Verification of Transportation Systems
  
  • Belabed Lilia
  • Tanzi Tullio
  • Coudert Sophie
  • Legros Dominique
  , 2017.
• A COMPLEX SPECTRUM BASED SAR IMAGE RESAMPLING METHOD WITH RESTRICTED TARGET SIDELOBES AND STATISTICS PRESERVATION
  
  • Abergel Rémy
  • Ladjal Saïd
  • Tupin Florence
  • Nicolas Jean-Marie
  , 2017.
• On high dimensional regression: computational and statistical perspectives
  
  • Salmon Joseph
  , 2017. This dissertation essentially covers the work done by the author as a `Maître de Conférences'' at the Laboratoire de Traitement et Communication de l'Information (LTCI), at Télécom ParisTech, since December 2012. During this period, the author strengthened his contributions to high-dimensional statistics and in particular sparse regression methods. In particular, the main focus of the dissertation is on computational aspects and to speed-up algorithms for Lasso-type problems, on means to better take into account the unknown noise and on corrections against the bias non-smooth convex regression methods suffer from. This report is not meant to present comprehensive description of the results developed by the author, but rather a synthetic view of his main contributions. The interested reader may consult the referenced articles for additional details and more precise treatment of the topics presented here.
• Contribution à la calibration des antennes actives pour applications radar
  
  • Chalumyan Taguhi
  , 2017. Les travaux effectués pendant cette thèse portent sur le développement d’une nouvelle méthode de calibration des antennes actives pour applications radars. La méthode de calibration, détaillée au cours de ce manuscrit, prend en compte les effets de bord et de couplage entre les éléments rayonnants du réseau, en les intégrant dans le procédé de calibration ; de plus, elle permet d’éviter les dégradations de diagramme de rayonnement qui peuvent être causés par les désadaptions lors d’un pointage et/ou d’une pondération. Le champ lointain est calculé par Matlab à partir des données du champ proche calculé par HFSS. Ensuite par rétro-propagation des données de champ lointain, on calcule l’éclairement de la surface de l’antenne. A partir d’un schéma électrique équivalent du réseau d’antennes, on optimise avec ADS les valeurs de l’éclairement afin d’obtenir le diagramme de rayonnement souhaité. Les valeurs résultantes correspondent aux constantes de calibration du réseau. Cette approche a le double avantage de permettre de traiter ensemble les informations de la partie circuit et de la partie rayonnante de l’antenne et d’obtenir les coefficients de calibration de manière automatique en respectant la réalité de l’antenne. Cette méthode peut être appliquée aux antennes réelles afin d’obtenir un diagramme de rayonnement souhaité. Le modèle numérique peut être amélioré en y intégrant les schémas électriques équivalents des circuits RF.