S³ seminar : Novel Algorithms for Automated Diagnosis of Neurological and Psychiatric Disorders

Séminaire le 28 Mars 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Hojjat ADELI, (The Ohio State University, Columbus, USA)


Novel algorithms are presented for data mining of time-series data and automated electroencephalogram (EEG)-based diagnosis of neurological and psychiatric disorders based on adroit integration of three different computing technologies and problem solving paradigms: neural networks, wavelets, and the chaos theory. Examples of the research performed by the author and his associates for automated diagnosis of epilepsy, the Alzheimer’s Disease, Attention Deficit Hyperactivity Disorder (ADHD), autism spectrum disorder (ASD), and Parkinson’s disease (PD) are reviewed.

Biography: Hojjat Adeli received his Ph.D. from Stanford University in 1976 at the age of 26. He is Professor of Civil, Environmental, and Geodetic Engineering, and by courtesy Professor of Biomedical Informatics, Biomedical Engineering, Neuroscience, and Neurology at The Ohio State University. He has authored over 550 publications including 15 books. He is the Founder and Editor-in-Chief of international research journals Computer-Aided Civil and Infrastructure, now in 32nd year of publication, and Integrated Computer-Aided Engineering, now in 25th year of publication, and the Editor-in-Chief of International Journal of Neural Systems. In 1998 he received the Distinguished Scholar Award from OSU, “in recognition of extraordinary accomplishment in research and scholarship”. In 2005, he was elected Distinguished Member, ASCE: "for wide-ranging, exceptional, and pioneering contributions to computing in civil engineering and extraordinary leadership in advancing the use of computing and information technologies in many engineering disciplines throughout the world.” In 2010 he was profiled as an Engineering Legend in the ASCE journal of Leadership and Management in Engineering, and Wiley established the Hojjat Adeli Award for Innovation in Computing. In 2011 World Scientific established the Hojjat Adeli Award for Outstanding Contributions in Neural Systems. He is a Fellow of IEEE, the American Association for the Advancement of Science, American Neurological Society, and American Institute for Medical and Biomedical Engineering. Among his numerous awards and honors are a special medal from Polish Neural Network Society, the Eduardo Renato Caianiello Award for Excellence in Scientific Research from the Italian Society of Neural Networks, the Omar Khayyam Research Excellence Award from Scientia Iranica, an Honorary Doctorate from Vilnius Gediminas Technical University, and corresponding member of the Spanish Royal Engineering Society.

Séminaire d'Automatique du plateau de Saclay : Controllability of a bent 3-link magnetic microswimmer

Séminaire le 23 Mars 2017, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Pierre Lissy (CEREMADE, Universite Paris-Dauphine)


A recent promising technique for moving a robotic micro-swimmer (in view notably of medical applications) is to apply an external magnetic field. In this talk, I will focus on a 3-link magnetic microswimmer, which consists of three rigid magnetized segments connected by two torsional springs, one of the springs being twisted, so that the swimmer is not aligned at rest. By acting on it with
an external magnetic field, the swimmer twists and moves through the surrounding fluid. After explaining some specific difficulties coming from the Low Reynolds number regime, I will explain how to model the problem thanks to a system of non-linear ODEs. By considering the external magnetic field as a control function, I will state a local partial controllability result around the equilibrium states. Then, I will propose a constructive method to find a magnetic field that allows the swimmer to move along a prescribed trajectory (tracking) in view of obtaining global partial controllability results. Finally, I will show some numerical simulations that illustrate the practical difficulties of the tracking method due to the straight positions of the swimmer. This is a joint work with Laetitia Giraldi (INRIA Sophia), Jean-Baptiste Pomet (INRIA Sophia) and Clément Moreau (ENS Cachan).

Bio: Pierre Lissy received his Ph.D degree in Applied Mathematics in 2013 under the direction of Professor Jean-Michel Coron at Université Pierre et Marie Curie. He is now Assistant Professor in Applied Mathematics at University Paris-Dauphine since 2014. His research interests include the controllability properties of partial differential equations (PDEs), with a focus on the controllability of (linear and non-linear) coupled systems of PDEs and the estimations of the cost of the control near the minimal time of control and in singular limits. He began recently to work on the controllability properties of magnetized micro-swimmers governed by non-linear ODEs.

Séminaire d'Automatique du plateau de Saclay : Time-extremal trajectories of generic control-affine systems have at most finite-order Fuller singularities

Séminaire le 23 Mars 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Francesco Boarotto (CMAP, Ecole Polytechnique)


Let $M$ be a smooth connected $n$-dimensional manifold, and consider on it the control-affine system $\dot{q}=f_0(q)+uf_1(q),\quad u\in[-1,1].$ Time-extremal trajectories for the time-optimal control problem associated to this system are driven by controls $u$, whose set $\Sigma$ of discontinuities is possibly stratified as follows: $\Sigma_0$ is the set of isolated points in $\Sigma$ (switching times) and, recursively, the $k$-th order Fuller times $\Sigma_k$ are found as the isolated points of $\Sigma\setminus\left(\bigcup_{j=0}^{k-1}\Sigma_j\right)$.

In this talk we show that, in fact, for the generic choice of the pair $(f_0,f_1),$ there exists an integer $N>0$ such that the control $u$ associated to any time-extremal trajectory admits at most Fuller times of order $N$. In particular, $u$ is smooth out of a set of measure zero. This is a joint work with M. Sigalotti (CMAP, Ecole Polytechnique).

Bio: Francesco Boarotto was born in Verona, Italie, in 1988. He received the Master's degree in mathematics from the University of Padou, Italie, in 2012 and the Ph.D degree from SISSA, Trieste, Italie, in 2016. Since then he has been post-doc in CMAP - Ecole Polytechnique. His research interests include geometric control theory and sub-Riemannian geometry.

 

S³ seminar : On Electromagnetic Modeling and Imaging of Defects in Periodic Fibered Laminates

Séminaire le 10 Mars 2017, 12h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Zicheng LIU, (Inverse problems Group, Signals and Statistics Division, L2S Laboratory)


Composite laminates are commonly utilized in industry due to advantages as high stiffness, light weight, versatility, etc. Multiple layers, each one involving periodically-positioned circular-cylindrical fibers in a given homogeneous matrix, are usually involved. However, defects can affect the structure and thereupon impact security and efficiency, and they call for nondestructive testing. By electromagnetic (EM) means, it requires fast and reliable computational modeling of both sound and damaged laminates if one wishes to better understand pluses and minuses of the testing, and derive efficient imaging algorithms for the end user. Both direct modeling and inverse imaging will be introduced in this presentation.  For the former, since the periodicity of the structure is destroyed due to defects, methods based on the Floquet theorem are inapplicable. Two modeling approaches are then utilized: one is with supercell methodology where a fictitious periodic structure is fabricated, so as the EM field solution everywhere in space can be well approximately modeled, provided the supercell be large enough; the other is based on fictitious source superposition (FSS) where defects are treated as equivalent sources and the field solution is a summation of responses to the exterior source and equivalent ones. For imaging, with MUSIC and sparsity-based algorithm, missing fibers could be accurately located.

Biography: Zicheng LIU was born in Puyang, China, in October 1988. He received the M.S. degree in circuit and system from Xidian University, Xi’an, China in March 2014 and is currently pursuing the Ph.D. degree with the benefit of a Chinese Scholarship Council (CSC) grant at the Laboratoire des Signaux et Systèmes, jointly Centre National de la Recherche Scientifique (CNRS), CentraleSupélec, and Université Paris-Sud, Université Paris-Saclay, Paris, France. He will defend his Université Paris-Saclay Ph.D. early Fall 2017. His present work is on the electromagnetic modeling of damaged periodic fiber-based laminates and corresponding imaging algorithms and inversion. His research interests include computational electromagnetics, scattering theory on periodic structures, non-destructive testing, sparsity theory, and array signal processing.

S³ seminar : On Imaging Methods of Material Structures with Different Boundary Conditions

Séminaire le 10 Mars 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Xiuzhu YE, (Beihang University, Beijing, China)


This talk is about the two-dimensional inverse scattering problems for different kinds of boundary conditions. Firstly, we propose a perfect electric conductor (PEC) inverse scattering approach, which is able to reconstruct PEC objects of arbitrary number and shape without requiring prior information on the approximate locations or the number of the unknown scatterers. Secondly, the modeling scheme of the T-matrix method is introduced to solve the challenging problem of reconstructing a mixture of both PEC and dielectric scatterers together. Then the method is further extended to the case of scatterers with four boundary conditions together. Last, we propose a method to solve the dielectric and mixed boundary through-wall imaging problem. Various numerical simulations and experiments are carried out to validate the proposed methods.

Biography: Xiuzhu YE was born in Heilongjiang, China, in December 1986. She received the Bachelor degree of Communication Engineering from Harbin Institute of Technology, China, in July 2008 and the Ph.D. degree from the National University of Singapore, Singapore, in April 2012. From February 2012 to January 2013, she worked in the Department E.C.E., National University of Singapore, as a Research Fellow. Currently, she is Assistant Professor in the School of Electronic and Information Engineering of the Beihang University. She has been and is engaged under various guises with Ecole Centrale de Pékin (ECPK) also. She is presently benefiting from an invited professorship position at University Paris-Sud and later this Summer 2017 she will be benefiting from an invited professorship position at CentraleSupélec, both within the Laboratoire des Signaux et Systèmes, jointly Centre National de la Recherche Scientifique (CNRS), CentraleSupélec, and Université Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, France. Her current research interest mainly includes fast algorithms in solving inverse scattering problems, near field imaging, biomedical imaging, and antenna designing.

Séminaire d'Automatique du plateau de Saclay : Computation of Curvature Penalized Shortest Paths via the Fast Marching Algorithm

Séminaire le 28 Février 2017, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Jean-Marie Mirebeau (Laboratoire de mathématique d'Orsay, Université Paris-Sud)


Motivated by applications to motion planning and image segmentation, we consider shortest paths models with a curvature penalization, such as the Euler/Mumford elasticas, or the Reed-Shepp car with or without reverse gear. Our numerical strategy, for computing the path of minimal energy joining two given points, involves approximating these singular models using strongly anisotropic Riemannian or Finslerian metrics on the product space R^d x S^{d-1}. The associated eikonal equations are then solved via specialized variants of the Fast-Marching algorithm.

Bio. Jean-Marie Mirebeau est chargé de recherches au Laboratoire de mathématiques d'Orsay, Université Paris-Sud, CNRS, Université Paris-Saclay. Ses travaux portent sur la résolution numérique des équations aux dérivées partielles, et en particulier sur les difficultés liées aux fortes anisotropies. C'est à dire à l'existence de directions privilégiées par le modèle, non alignées avec les axes de coordonnées. La conception de schémas pour ces modèles requiert des outils mathématiques peu communs en analyse, souvent issus de l'arithmétique et de la géométrie discrète. Son activité englobe l'étude théorique de la convergence et de la complexité des schémas numériques, leur implémentation et leur distribution en license libre, et le suivi de leur application via des collaborations académiques et industrielles. Jean-Marie Mirebeau a reçu le prix Popov 2016 pour ses contributions en théorie de l'approximation. Il était antérieurement affecté au laboratoire Ceremade de l'Université Paris-Dauphine, et a effectué sa thèse sous la direction d'Albert Cohen à l'Université Pierre et Marie Curie.

Séminaire d'Automatique du plateau de Saclay : A relaxation result for state constrained delay differential inclusion

Séminaire le 28 Février 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Ihab Haidar (Laboratoire Quartz, ENSEA-CERGY)


This talk is interested by delay differential inclusions in finite dimensional real space. The celebrated Filippov’s theorem is extended to this case. Then, this theorem is generalized to the case when the state variable is constrained to the closure of an open state subset. Under a new “inward pointing condition”, a relaxation result stating that the set of trajectories lying in the interior of the state constraint is dense in the set of constrained trajectories of the convexified inclusion is shown.
Bio. Ihab Haidar was born in Beirut, Lebanon, in 1983. He received the Master’s degree in mathematics from the University of Aix-Marseille 1, France, in 2008 and the Ph.D degree from the University of Montpellier 2, France, in 2011. Since then he has been post-doc in different places (Laboratoire des Signaux et Systèmes, Institut de Mathématiques de Jussieu, Laboratoire QUARTZ-ENSEA). His research interests include control theory, time delay systems and systems biology.

S³ seminar : FastText: A library for efficient learning of word representations and sentence classification

Séminaire le 24 Février 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Piotr Bojanowski, (Facebook AI Research)


In this talk, I will describe FastText, an open-source library that can be used to train word representations or text classifiers. This library is based on our generalization of the famous word2vec model, allowing to adapt it easily to various applications. I will go over the formulation of the skipgram and cbow models of word2vec and how these were extended to meet the needs of our model. I will describe in details the two applications of our model, namely document classification and building morphologically-rich word representations. In both applications, our model achieves very competitive performance while being very simple and fast.

Séminaire d’Automatique du plateau de Saclay : Cooperative Control of Multi-Agents: On a Sphere Manifold and in the Euclidean Space

Séminaire le 13 Février 2017, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Wei Li (Department of Control and Systems Engineering, Nanjing University)


The talk will discuss cooperative control of multi-agents on a sphere and in the Euclidean space. We will first consider the control law design of agents on a sphere, and analyze the stability, scaling, and geometry properties, and discuss future directions. Then, for agents evolving in the Euclidean space, we will consider coupled agents with second-order dynamics. The state of a single agent includes both position and velocity, thus generally, the agents have both velocity coupling and position couplings (VCPC); and if we consider different VCPC, then interesting yet difficult problems arise. We then discuss two aspects of analysis on consensus convergence , and future directions.

Bio. Wei Li received the Ph.D. degree in Automatic Control from Shanghai Jiao Tong University, Shanghai, China, in 2008.
From 2009 to 2010, he was a Post-Doctoral Research Associate with the Department of Electrical Engineering, The University of Texas at Dallas, Dallas, TX, USA. Since 2010, he has been an Associate Professor with the Department of Control and Systems Engineering, Nanjing University, Nanjing, China. His current research interests include robotics, autonomous mobile robots, decentralized control, cooperative control of mobile robotic agents, and wireless sensor networks. Dr. Li is an Associate Editor of Asian Journal of Control. He is a Senior Member of IEEE.

Séminaire d’Automatique du plateau de Saclay : Observer synthesis under time-varying sampling for Lipschitz nonlinear systems

Séminaire le 13 Février 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Lucien Etienne (L2S, CentraleSupelec)


The problem of observation of continuous-time nonlinear Lipschitz systems under time-varying discrete measurements is studied. This class of systems naturally occurs when continuous processes are observed through digital sensors and information is sent via a network to a computer for state estimation. Since network introduces uncertainties in the sampling time, the observer must be designed so to take these uncertainties into account. Here two classes of observation scheme are studied. First an impulsive observers, which make instantaneous correction when information is received, is considered. Then a Luenberger-like observer with a piece wise constant correction term is studied. For both classes of observer, generic conditions are provided. Then a restriction of the generic conditions is used to establish tractable conditions that allows the synthesis of an observer gain.
Bio. Lucien Etienne received a M.Sc. Degree in Applied Mathematics at the INSA Rouen in 2012 and a joint Ph.D. in Automatic Control from the university of L'Aquila and the university of Cergy-Pontoise in 2016. After a Post-doc at INRIA Lille on observer synthesis for sampled data system, he is currently Post-doc at L2S CentralSupéléc working on switched systems for embedded control under mixed stochastic/deterministic timing uncertainty.

His research interests include switched and hybrid systems, Observer synthesis and sampled data systems.

S³ seminar : Stochastic Quasi-Newton Langevin Monte Carlo

Séminaire le 10 Février 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Umut Şimşekli, (LTCI, Télécom ParisTech)


Recently, Stochastic Gradient Markov Chain Monte Carlo (SG-MCMC) methods have been proposed for scaling up Monte Carlo computations to large data problems. Whilst these approaches have proven useful in many applications, vanilla SG-MCMC might suffer from poor mixing rates when random variables exhibit strong couplings under the target densities or big scale differences. In this talk, I will present a novel SG-MCMC method that takes the local geometry into account by using ideas from Quasi-Newton optimization methods. These second order methods directly approximate the inverse Hessian by using a limited history of samples and their gradients. Our method uses dense approximations of the inverse Hessian while keeping the time and memory complexities linear with the dimension of the problem. I will provide formal theoretical analysis where it is shown that the proposed method is asymptotically unbiased and consistent with the posterior expectations. I will finally illustrate the effectiveness of the approach on both synthetic and real datasets. This is a joint work with Roland Badeau, Taylan Cemgil and Gaël Richard. arXiv: https://arxiv.org/abs/1602.03442

S³-PASADENA seminar : Detecting confounding in multivariate linear models via spectral analysis

Séminaire le 31 Janvier 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Dominik Janzing, Max Planck Institute for Intelligent Systems, Tuebingen, Germany


We study a model where one target variable Y is correlated
with  a vector X:=(X_1,...,X_d) of predictor variables  being potential causes of Y.
We describe  a method that infers to what extent the statistical dependences between X and Y
are due to the influence of X on Y and to what extent due to a hidden common cause
(confounder) of X and Y. The method is based on an independence assumption stating that, in the absence of confounding,
the vector of regression coefficients describing the influence of each X on Y has 'generic orientation'
relative to the eigenspaces  of the covariance matrix of X. For the special case of a scalar confounder we show that confounding typically spoils this generic orientation in a characteristic way that can be used to quantitatively estimate the amount of confounding.
I also show some encouraging experiments with real data, but the method is work in progress and critical comments are highly appreciated.

Postulating 'generic orientation' is inspired by a more general postulate stating that
P(cause) and P(effect|cause) are independent objects of Nature and therefore don't contain information about each other [1,2,3],
an idea that inspired several causal inference methods already, e.g. [4,5].

[1] Janzing, Schoelkopf: Causal inference using the algorithmic Markov condition, IEEE TIT 2010.
[2] Lemeire, Janzing: Replacing causal faithfulness with the algorithmic independence of conditionals, Minds and Machines, 2012.
[3] Schoelkopf et al: On causal and anticausal learning, ICML 2012.
[4] Janzing et al: Telling cause frome effect based on high-dimensional observations, ICML 2010.
[5] Shajarisales et al: Telling cause from effect in deterministic linear dynamical systems, ICML 2015.

Feedback transformations of underactuated mechanical systems for trajectory planning: case studies in non-prehensile manipulation

Séminaire le 26 Janvier 2017, 14h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Anton SHIRIAEV (Department of Engineering Cybernetics, NTNU, Norway)


The talk is aimed at discussion of challenges present in developing model based trajectory planning algorithms for underactuated mechanical systems. Nonlinearity of system’s dynamics and presence of one or several passive degrees of freedom are among several structural properties that are difficult to handle in a trajectory search. Other challenges are related to different formats of representation of feasible trajectories, where some choices can be better suited for further stabilization or advantageous in sensitivity analysis with respect to uncertainty in system parameters. The author is interested to emphasize the attention on two relatively new points in the problem that have recently helped in solving a series of longstanding manipulation problems in robotics: change of coordinates and feedback transformation for mechanical systems are useful to formulate as dependent on an individual trajectory even though such a feasible behavior is not found yet. The arguments are illustrated by new analytical results and the case study in non-prehensile manipulation.

Feedback transformations of underactuated mechanical systems for trajectory planning: case studies in non-prehensile manipulation

Séminaire le 26 Janvier 2017, 14h30 à CentraleSupelec (Gif-sur-Yvette) Amphi F3-09
Anton SHIRIAEV (Department of Engineering Cybernetics, NTNU, Norway)


The talk is aimed at discussion of challenges present in developing model based trajectory planning algorithms for underactuated mechanical systems. Nonlinearity of system’s dynamics and presence of one or several passive degrees of freedom are among several structural properties that are difficult to handle in a trajectory search. Other challenges are related to different formats of representation of feasible trajectories, where some choices can be better suited for further stabilization or advantageous in sensitivity analysis with respect to uncertainty in system parameters. The author is interested to emphasize the attention on two relatively new points in the problem that have recently helped in solving a series of longstanding manipulation problems in robotics: change of coordinates and feedback transformation for mechanical systems are useful to formulate as dependent on an individual trajectory even though such a feasible behavior is not found yet. The arguments are illustrated by new analytical results and the case study in non-prehensile manipulation.

Séminaire d’Automatique du plateau de Saclay : What drives the quality of local public goods in Africa? Disentangling social capital and ethnic divisions

Séminaire le 24 Janvier 2017, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Guillaume Hollard (Département d’Economie, Ecole polytechnique)


Two important lines of research shaped our understanding of the ability of communities to engage in collective action. The first line proposes ethnic division as a key determinant, with more ethnically heterogeneous countries having lower economic performances and levels of public goods. Thus, we expect to find better schools where ethnic fractionalization is low. The second line of research focuses on social capital as a major determinant of the ability to engage in collective action.We expect that trust among community members, a widely-used measure of social capital, is an important and positive determinant of school quality. The present work aims to disentangle the relative effects of ethnic fractionalization and social capital on school quality. We use instrumental variable estimations to address reverse causality and other endogeneity issues. We instrument both social capital and ethnic fractionalization by using historical information on the settlement patterns of ethnic groups in Sub-Saharan Africa. Our empirical strategy is implemented by combining four datasets, including Afrobarometer, covering 16 Sub-Saharan countries. We run our analysis at the district level, with more than 1000 districts covered. We find an important and positive effect of trust on the practical aspects of schooling, such as maintaining buildings or providing textbooks. A one percent increase in the level of trust increases the quality of local public goods by 0.18 to 1.05 percent, depending on the measure of school quality under consideration. In sharp contrast, ethnic fractionalization is found to have a very limited effect, if any. We propose a simple model of public good provision that explores a channel by which social capital and ethnic division may (or may not) have an impact on the provision of local public goods such as schools. Our results suggest that policies designed to enhance social capital are likely to have a positive effect on schools and local public goods in general.

Bio. Directeur de recherche au CNRS et professeur associé à l'école polytechnique. Spécialisé dans l'analyse de la décision et du comportement. Responsable du laboratoire d'économie expérimentale.

Séminaire d’Automatique du plateau de Saclay : Moral hazard with mean field type interactions

Séminaire le 24 Janvier 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Thibault Mastrolia (CMAP, Ecole Polytechnique)


We investigate a moral hazard problem in finite time with lump-sum and continuous payments, involving infinitely many Agents, with mean field type interactions, hired by one Principal. By reinterpreting the mean-field game faced by each Agent in terms of a mean field FBSDE, we are able to rewrite the Principal’s problem as a control problem for McKean-Vlasov SDEs. We solve completely and explicitly the problem in special cases, going beyond the usual linear-quadratic framework.

Bio. Après avoir effectué un magistère de mathématiques à l'université de Strasbourg puis le M2 MASEF de l'université Paris-Dauphine, j'ai poursuivi mes études par un doctorat au sein de cette université sous la direction d'Anthony Réveillac et de Dylan Possamaï autour du calcul de Malliavin, des EDSR et de leurs applications en finance. J'ai ensuite été recruté comme Maître de conférences en probabilités et mathématiques financières à l'Ecole Polytechnique. Actuellement, je travaille autour de problèmes de théorie des contrats et de leurs applications.

S³ Seminar: Adapting to unknown noise level in super-resolution

Séminaire le 20 Janvier 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Claire Boyer (LSTA, UPMC)


We study sparse spikes deconvolution over the space of complex-valued measures when the input measure is a finite sum of Dirac masses. We introduce a new procedure to handle the spike deconvolution when the noise level is unknown. Prediction and localization results will be presented for this approach. An insight on the probabilistic tools used in the proofs could be briefly given as well.

S³ seminar : Inverse problems for speech production

Séminaire le 20 Janvier 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Benjamin Elie (LORIA, IADI)


Studies on speech production are based on the extraction and the analysis of the acoustic features of human speech, and also on their relationships with the articulatory and phonatory configurations realized by the speaker. An interesting tool, which will be the topic of the talk, to make such researches is the articulatory synthesis, which consists in the numerical simulation of the mechanical and acoustical phenomena that are involved in speech production. The aim is to numerically reproduce a speech signal that contains the observed acoustic features with regards to the actual articulatory and phonatory gestures of the speaker. Using the articulatory approach may lead to a few problems that will be tackled in this talk, and to which possible solutions will be discussed. Firstly, the different articulatory gestures realized in natural speech should be precisely observed. For that purpose, the first part of the talk focuses on methods to acquire articulatory films of the vocal tract by MRI techniques with a fast acquisition rate via sparse techniques (Compressed Sensing). The aim is, in fine, to build an articulatory and a coarticulation model. The investigation of the acoustical phenomena involved in natural speech require to separate the contributions of the different acoustic sources in the speech signal. The periodic/aperiodic decomposition of the speech signal is the subject of the second part of the talk. The challenge is to be able to study the acoustic properties of the frication noise that is generated during the production of fricatives, and also to quantify the amount of voicing produced during fricatives. Finally, in order to directly use the analysis by synthesis methods, it is interesting to estimate the articulatory configurations of the speaker from the acoustic signal. This is the aim of the acoustic-articulatory inversion for copy synthesis, which is the third part of the talk. Direct applications of these problems for the study of speech production and phonetics will be presented.

Séminaire d’Automatique du plateau de Saclay : Fokker-Planck optimal control for stochastic processes

Séminaire le 13 Décembre 2016, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Mario Annunziato (Università degli Studi di Salerno)


An innovative framework for the control of stochastic process by means of an optimization problem on the Fokker-Planck equation is presented. The time dependent probability density function (PDF)  as representative of the dynamical state of a stochastic system is used, hence the governing Kolmogorov-Fokker-Planck-type (KFP) equation is employed as a constraint for the minimization of a cost function. The problem to find a controller that minimizes the cost function can be solved by solving an optimality system of time dependent forward and backward partial differential equations. A short review of control objectives, KFP equations and numerical techniques to tackle the optimization problem, is shown by using models from biology, physics, and finance.

Bio. Mario Annunziato is a researcher in Mathematics, in the field of Numerical analysis at "Università degli Studi di Salerno" since 2004. He is also a member of "Gruppo Nazionale di Calcolo Scientifico, Instituto Nazionale di Alta Mathemaica". He has received his Ph.D. degree in Physics at " Università degli Studi di Pisa" in 2000. He obtained a degree of laurea in Physics at "Rome University - La Sapienza" in 1995.

His research interests focus on numerical solutions of time dependent Partial Differential Equations (PDE) and Integral Equations, related to stochastic processes and stochastic optimal control.

S³ seminar: High dimensional sampling with the Unadjusted Langevin Algorithm

Séminaire le 23 Novembre 2016, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Alain Durmus (LTCI, Telecom ParisTech)


Recently, the problem of designing MCMC sampler adapted to high-dimensional distributions and with sensible theoretical guarantees has received a lot of interest. The applications are numerous, including large-scale inference in machine learning,  Bayesian nonparametrics, Bayesian inverse problem, aggregation of experts among others. When the density is L-smooth (the log-density is continuously differentiable and its derivative is Lipshitz), we will advocate the use of a “rejection-free” algorithm, based on the discretization of the  Euler diffusion with either constant or decreasing stepsizes. We will present several new results allowing convergence to stationarity under different conditions for the log-density (from the  weakest, bounded oscillations on a compact set and super-exponential in the tails to the log concave).
When the density is strongly log-concave, the convergence of an appropriately weighted empirical measure is also investigated and bounds for the mean square error and exponential deviation inequality for Lipschitz functions will be reported.
Finally, based on optimzation techniques we will propose new methods to sample from high dimensional distributions. In particular, we will be interested  in densities which are not continuously differentiable. Some Monte Carlo experiments will be presented to support our findings.

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