# Publications

Lecture notes

Optimisation (french). Some slides of a Graduate "refrecher" course are available here.

Wavelet theory (french), available soon. Here is a handwritten draft.

Submitted

A finite sample analysis of the benign overfitting phenomenon for ridge function estimation (with Emmanuel Caron), submitted.

Post-Prognostics Decision for Optimizing the Commitment of Fuel Cell Systems, (with Nathalie Herr, J.-M. Nicod and C. Varnier), in revision for Maths in Action.

Hedging parameter selection for basis pursuit (with A. Gibberd and S. Roy), ArXiv preprint (2018).

Journal papers, conferences with long papers, and some unpublished manuscripts.

The realisation of fast X-ray computed tomography using a limited number of projection images for dimensional metrology, (with Ander Biguri, Manuchehr Soleiman, Thomas Blumensath, Jessica Goldring and Wenjuan Sun), NDT and E International, to appear.

The active nonsmooth manifolds of a neural network classifier: a tool for confidence assessment, Stéphane Chrétien, Volodimir Mitarchuk and Julien Velcin, Computing Conference 2023, London, Lecture Notes in Network Science, to appear.

Using Data Science to predict firemen interventions: a case study. Christophe Guyeux, Gaby Bou Tayeh, Abdallah Makhoul, Stéphane Chrétien, Julien Bourgeois and Jacques M. Bahi, Journal of Supercomputing, to appear.

An SDP dual relaxation for the Robust Shortest Path Problem with ellipsoidal uncertainty: Pierra’s decomposition method and a new primal Frank-Wolfe-type heuristics for duality gap evaluation, Chifaa Dahik, Zeina Al Masry, Stephane Chretien, Jean-Marc Nicod, Landy Rabehasaina, Mathematics, to appear.

Learning with Semi-Definite Programming: new statistical bounds based on fixed point analysis and excess risk curvature (with Mihai Cucuringu, Guillaume Lecue and Lucie Neirac), Journal of Machine Learning Research, 22 (230), 2021.

Low tubal rank tensor recovery using the Bürer-Monteiro factorisation approach. Application to optical coherence tomography, (with Mohamed Assoweh and Brahim Tamadazte), Journal of Computational and Applied Mathematics, to appear.

Revisiting clustering as matrix factorisation on the Stiefel manifold, (with Benjamin Guedj), Proceedings of LOD 2020, Lecture Notes in Computer Science, to appear.

Fast hyperparameter calibration of sparsity enforcing penalties in Total Generalised Variation penalised reconstruction methods for XCT using a planted virtual reference image (with Camille Giampiccolo, Wenjuan Sun and Jessica Talbott), Mathematics, to appear.

Ant Colony-Based Hyperparameter Optimisation in Total Variation Reconstruction in X-ray Computed Tomography, (with M. Lohvithee, W. Sun and M. Soleimani), Sensors, Special Issue Tomography Sensing Technologies, 2021, 21(2), 591; https://doi.org/10.3390/s21020591 .

Boolean learning under noise-perturbations in hardware neural networks, Louis Andreoli, Xavier Porte, Stéphane Chrétien, Maxime Jacquot, Laurent Larger, and Daniel Brunner, Nanophotonics, to appear.

Cyclic Projection Methods for Uniformly Convex Expandable Set (with Pascal Bondon), Mathematics 2020, 8(7), 1108.

Multi-kernel unmixing and super-resolution using the Modified Matrix Pencil method (with Hemant Tyagi), Journal of Fourier Analysis and Applications, 26(1), (2020). Matlab code for comparison between Modified Matrix Pencil and MUSIC is here.

Clustering on Laplacian-embedded latent manifolds when clusters overlap (with K. Jagan and E. Barton), Measurement Science and Technology, Volume 31, Number 11 (2020).

3-dimensional OCT compressed sensing using the shearlet transform under continuous trajectories sampling, (with B. Haydar, B. Tamadazte, N. Andreev), Informatics in Medicine Unlocked, Volume 19, (2020).

Tensor Completion using the t-SVD and Nuclear Norm Minimization with Application to OCT Image Recovery, (with B. Tamadazte and Assoweh Mohamed), Mathematics 8 (4), 628, (2020).

Efficient hyper-parameter selection in total variation based CT reconstruction using Freund and Shapire Hedge approach, (with M. Lohvithee, W. Sun and M. Soleimani), Mathematics, 8(4), p.493, (2020).

On Clustering Methods For Massive Data Management In The Internet of Things, (with C. Guyeux *, G. Bou Tayeh, J. Demerjian, J. Bahi), Special Issue "Massive Sensory Data Management in WSN, IoT and CPS", Journal of Sensor and Actuator Networks 8 (4), 56 (2020).

On a new method for controlling the entire spectrum in the problem of column selection (with Sebastien Darses), Expositiones Mathematicae, Volume 37, Issue 3, Pages 314-321, (2019).

A Semi-Definite Programming approach to low dimensional embedding for unsupervised clustering, (with C. Dombry and A. Faivre), Frontiers in Applied Mathematics and Statistics (2019).

SpCLUST: towards a fast and reliable clustering for potentially divergent biological sequences (with J. Matar, H. El Khoury, J-C. Charr and C. Guyeux), Computers in biology and medicine, 114, (2019).

The dual approach to non-negative super-resolution: impact on primal reconstruction accuracy (with Andrew Thompson and Bogdan Toader), SAMPTA 2019 (long version forthcoming), (2019).

Decomposition of dynamical signals into jumps, oscillatory patterns and possible outliers (with E. Barton, B. Al Sarray and K. Jagan), Mathematics, 6(7), p.124 (2018) .

Average performance analysis of the stochastic gradient method for online PCA, (with C. Guyeux and Z.-W. O. Ho), Lecture Notes in Computer Science, Proceedings of LOD 2018, Volterra, (2018).

Feature extraction using column selection (with Olivier Ho), In: Deville Y., Gannot S., Mason R., Plumbley M., Ward D. (eds) Latent Variable Analysis and Signal Separation. LVA/ICA 2018. Lecture Notes in Computer Science, vol 10891. Springer, Cham, (2018).

A simple formula for the Hilbert metric with respect to a subgaussian cone (with Juan-Pablo Ortega), Mathematics, 6(3) 35, (2018).

On the subdifferential of symmetric convex functions of the spectrum for symmetric and orthogonally decomposable tensors. Linear Algebra and its Applications, (with T. Wei), 542, 1 pp. 84-100, (2018).

Application of Robust PCA with structured outlier matrix to topology estimation in power grids (with Paul Clarkson and Maria Segovia-Garcia), International Journal of Electrical Power and Energy Systems, 100, pp. 559-564, (2018).

A fast algorithm for the Semi-Definite relaxation of the state estimation problem in power grids (with Paul Clarkson), Journal of Industrial and Management Optimization, (2018).

A clustering tool for nucleotide sequences using Laplacian Eigenmaps and Gaussian Mixture Models, (with Marine Bruneau, Thierry Mottet, Serge Moulin, Maël Kerbiriou, Franz Chouly and Christophe Guyeux ), Computers in Biology and Medicine, 93, pp. 66-74, (2018).

A note on computing the Smallest Conic Singular Value, Journal of Computational and Applied Mathematics, 340(1) , pp. 221-230 , 2018. Note: there is a factor 1/2 missing in front of sigma_{\min}(A;K)^2 in eq. (2.1), in Theorem 2.2 and Corollary 2.3.

Study of Gear Surface Texture Using Mallat's Scattering Transform, (with W. Sun, R. Hornby, P. Cooper, A. Lancaster, R. Frazer and J. Zhang), Proceedings of the AMCTMT 2017 conference, Strathclyde, World Scientific (2017).

Systematic investigations of gene effects on both topologies and supports: an Echinococcus illustration (with C. Guyeux, N. M.-L. Côté and J. M. Bahi), Journal of Bioinformatics and Computational Biology, 15 (5), (2017).

An elementary approach to the problem of column selection in a rectangular matrix (with S. Darses), Lecture Notes in Computer Science, Proceedings of MOD 2017, Optimization, and Big Data, pp. 234-243. Lecture Notes in Computer Science, Springer, Cham, (2017).

On the pinning controllability of complex networks using perturbation theory of extreme singular values. Application to synchronisation in power grids, (with S. Darses, C. Guyeux and P. Clarkson), Numerical Algebra, Control and Optimization, 7 (3), pp. 289 - 299, (2017) .

Sensing tensors with Gaussian filters, IEEE Trans. Information Theory (with T. Wei), 63 (2), pp. 843-852, (2017).

Enhancing Prony's method by nuclear norm penalization and extension to missing data, Signal, Image and Video Processing (with B. Al-Sarray, P. Clarkson and G. Cottez), 11 (6), pp. 1089–1096, (2017).

Simulation-based estimation of branching models for LTR retrotransposons, Bioinformatics (with S. Moulin, N. Seux, C. Guyeux, E. Lerat, et al., 33 (3), pp. 320-326, (2016).

A Bregman-proximal point algorithm for robust non-negative matrix factorization with possible missing values and outliers-application to gene expression analysis (with C. Guyeux, B. Conesa, R. Delage-Mouroux, P. Huetz, M. Jouvenot, F. Descotes), BMC Bioinformatics 17 (8), 284 (2016).

A lower bound on the expected optimal value of certain random linear programs and application to shortest paths in Directed Acyclic Graphs and reliability (with F. Corset), Statistics & Probability Letters 117, pp. 221-230 (2016).

Dendrochemical assessment of mercury releases from a pond and dredged-sediment landfill impacted by a chlor-alkali plant (with F. Maillard, O. Girardclos, M. Assad, C. Zappelini, J. Maria Pérez Mena, L. Yung, C. Guyeux, G. Bigham, C. Cosio, M. Chalot), Environmental research, 148, pp. 122-126 (2016).

Gene expression signature functional annotation of breast cancer tumors in function of age, (with P. Jezequel et al.) BMC Medical Genomics (2015)

Job scheduling using successive linear programming approximations of a sparse model, (with J-M Nicod, L Philippe, V Rehn-Sonig and L Toch), Concurrency and Computation: Practice and Experience, 27, 14, pp 3561-3586 (2015)

Von Neumann's trace inequality for tensors (with T. Wei), Linear Algebra and its Applications, 482, 1, pp 149-157 (2015)

On the spacings between the successive zeros of the Laguerre polynomials (with S. Darses), Proceedings of the AMS, 143, 10, pp 4383-4388 (2015)

Convex recovery of tensors using nuclear norm penalization (with T. Wei), International Conference on Latent Variable Analysis and Signal Separation, LNCS 9237, 360-367 (2015). Springer, Cham.

Estimation of Gaussian mixtures in small sample studies using l1 penalization, Annales de l'ISUP 59, 23-36, (2015)

Sparse recovery with unknown variance: a LASSO-type approach (with S. Darses), IEEE Trans Information Theory, 60, 7, pp 3970-3988, (2014)

Multivariate GARCH estimation via a Bregman-proximal trust-region method (with J.-P. Ortega), Computational Statistics and Data Analysis, 76, pp 210-236, (2014)

Perturbation bounds on the extremal singular values of a matrix after appending a column, (with S. Darses), ArXiv (2014)

High-overtone Bulk Acoustic Resonator as passive Ground Penetrating RADAR cooperative targets,(with J.-M. Friedt, A. Saintenoy, T. Baron, E. Lebrasseur, T. Laroche, S. Ballandras, M. Griselin), Journal of Applied Physics, 113, 134904, (2013)

On prediction with the LASSO when the design is not incoherent, ArXiv preprint (2012)

Invertibility of random submatrices via tail decoupling and a Matrix Chernoff Inequality, (with S. Darses), Statistics and Probability Letters, 82, 7, pp 1479-1487, (2012)

EM type algorithms for likelihood optimization with non-differentiable penalties, (with A. O. Hero and H. Perdry), Ann Inst Stat Math, 64, 4, pp 791-809, (2012)

On the generic uniform uniqueness of the LASSO estimator, (with S. Darses), ArXiv preprint (2011)

An alternating l1 relaxation for compressed sensing, IEEE Signal Processing Letters, 17, 2, pp 181-184, (2010).

Mixtures of GAMs for habitat suitability analysis with overdispersed presence/absence data. (with D. Pleydell) Computational statistics & data analysis, 54(5), 1405-1418, (2010).

Using the eigenvalue relaxation for binary least-squares estimation problems (with F. Corset). Signal Processing, 89 (11), 2079-2091, (2009).

On EM algorithms and their proximal generalizations (with A. O. Hero) ESAIM: Probability and Statistics, 12, 308-326, (2008).

Physique statistique et optimisation combinatoire, Reperes IREM 61, (2005).

Degeneracy in the maximum likelihood estimation of univariate Gaussian mixtures with EM (with C. Biernacki). Statistics & probability letters, 61(4), 373-382, (2003).

A component-wise EM algorithm for mixtures (with G. Celeux, F. Forbes and A. Mkhadri). Journal of Computational and Graphical Statistics (2002).

Kullback proximal algorithms for maximum-likelihood estimation (with A. Hero). IEEE transactions on information theory, 46(5), 1800-1810, (2000).

Cyclic projection methods on a class of nonconvex sets (with P. Bondon). Numer. Funct. Anal. Optim. 17, no. 1-2, 37-56, (1996).

See Google Scholar for a full publication list. See also my ResearchGate page for details on my projects.

Conferences

Learning in graphs with semi-definite programming: statistical bounds based on fixed point analysis and excess risk curvature, Statistical Learning on Large Scale Graphs, Invited Speaker (1 hour talk) INRIA Lille, 9-10 march 2023.

Relationship between sample size and architecture for the estimation of Sobolev functions using deep neural networks, Apprentissage et Optimisation à Luminy - LOL2022, Learning and Optimization in Luminy - LOL2022, 3-7 October, 2022. Video

Point cloud registration for algebraic varieties using Riemannian optimization, (with Florentin Goyens and Coralia Cartis), 10th International Conference on Curves and Surfaces, June 20th to June 24th, 2022.

Benign overfitting of fully connected Deep Nets:A Sobolev space viewpoint, (with Emmanuel Caron), ESANN 2021.

The Quantile Matching Problem and Point Cloud Registration, (with Mustafa Pinar, Oya Ekin Karasan, Ecenur Oguz), SIAM Conference on Applied and Computational Discrete Algorithms (ACDA21).

Smoothing of point clouds using Riemannian optimization, (with Coralia Cartis and Florentin Goyens), ICML 2020, "Beyond first order methods in ML systems" workshop.

Revisiting clustering as matrix factorisation on the Stiefel manifold, (with Benjamin Guedj), proceedings of LOD 2020, Lecture Notes in Computer Science, to appear.

Using Frank-Wolfe as a Relaxation-Guided Solver for a Class of Robust Combinatorial Problems with an Ellipsoidal Uncertainty (with C. Al Dahik, Z. Al Masry, J.-M. Nicod and L. Rabehasaina ) Set, SIGOPT 2020.

Is spectral clustering mode preserving ? EGC 2020, Brussels. Accepted as poster presention.

Langevin sampling for median of means based estimation, CM-Statistics 2019, London.

Median of means estimation for high dimensional time series, CFE 2019, London.

General considerations for neural networks implemented in hardware, (with Daniel Brunner, Louis Andreoli, Javier Porte, Nadezhda Semenova, Maxime Jacquot, Stéphane Chretien, Stephan Reitzenstein, Laurent Larger), Photonica, Belgrad, 2019.

Greedy Boolean Learning in Photonic Recurrent Neural Network (with Louis Andreoli, Javier Porte, Maxime Jacquot, Laurent Larger, Daniel Brunner, Jan Große, Tobias Heuser, Stephan Reitzenstein), European Material Research Society annual meeting, Warshaw, 2019.

Incoherent submatrix selection via approximate independence sets in scalar product graphs, (with Oliver Ho), LOD 2019, Sienna.

Colloquium talk at Mathematics Department, University of Surrey https://www.surrey.ac.uk/events/20190522-partial-overview-recent-trends-mathematical-analysis-deep-

G. Frangou, I. Rungger and S. Chretien, The first quantum co-processor hybrid for processing quantum point cloud multimodal sensor data, Future Technologies Conference (FTC), San Francisco, October 24-25, 2019.

S. Chretien, B. Tamadazte and M. Assoweh Mohamed, Low tubal rank tensor recovery using the Burer-Monteiro factorisation approach, ICCOPT 2019, Berlin (could not attend neither present due to last minute personal constraints).

S. Chretien, A. Thompson and B. Toader, The dual approach to non-negative super-resolution: impact on primal reconstruction accuracy , ICCOPT 2019, Berlin.

S. Chretien and T. Wei, A penalized autoencoder approach for nonlinear independent component analysis, ICASSP 2019, Brighton.

Incoherent submatrix selection via approximate independence sets in scalar product graphs, (with Oliver Ho), Lecture Notes in Computer Science, Proceedings of LOD 2019, Sienna.

Efficient online Laplacian eigenmap computation for dimensionality reduction in molecular phylogeny via optimisation on the sphere, (with C. Guyeux), IWBBIO 2019, Lecture Notes in Bio-Informatics, Springer Verlag.

l1-penalised ordinal polytomous regression estimators (with C. Guyeux and S. Moulin), 18th International Workshop on Algorithms in Bioinformatics (WABI 2018), Dagstuhl Publications, Laxmi Parida and Esko Ukkonen (Eds.)

S. Chretien and C. Guyeux, Efficient online Laplacian eigenmap computation for dimensionality reduction in molecular phylogeny via optimisation on the sphere, IWBBIO 2019, Granada, May 8-10 2019.

S. Chretien, Clustering in polynomial time, 10th Computational Social Science Workshop, November 21, 2018.

S. Chretien, Clustering using low rank matrix estimation, CM-Statistics 2018, Pisa.

B. Al Sarray and S. Chretien, An ADMM for State Space model estimation via convex optimization using a nuclear norm penalization approach, SICAPM 2019, Bagdad.

S. Chretien, C. Guyeux and Olivier Ho, Average Performance Analysis of the Projected Gradient Method for Online PCA , LOD 2018, Volterra.

S. Chretien and Paul Clarkson, Handling Error in Variables in Linear and Quadratic Regression Using a Stochastic Gradient Method: Application to State Estimation in Power Grids, ENBIS 2018, Nancy.

S. Chretien and O. Ho, Feature extraction using column selection: a simple approach via perturbation theory of singular values, LVA-ICA 2018, University of Surrey, 2-6 July 2018.

S. Chretien, Manasavee Lohvithee and Wenjuan Sun, Hyper-parameter selection for accurate reconstruction in XCT tomography, D-XCT Conference Nottingham, July 2-3, 2018.

S. Chretien, A new and simpler approach to the analysis of Robust PCA, 6th IMA Conference on Numerical Linear Algebra and Optimization, University of Birmingham, 27-29 June 2018.

A. Thompson, A. Eftekhari and S. Chrétien, Dual approaches to grid-free sparse inverse problems, 6th IMA Conference on Numerical Linear Algebra and Optimization, University of Birmingham, 27-29 June 2018.

S. Chretien, Laplacian Signal Embedding for linear and non-linear AR , CM-Statistics 2017, Senate House, University of London, UK.

S. Chretien, Adaptive online model selection for linear and non-linear AR , Workshop on dynamical systems and brain inspired information processing, 5-6 October 2017, Universitat Konstanz.

S. Chretien and S. Darses, An elementary approach to the problem of column selection in a rectangular matrix, MOD 2017, Volterra, Italy.

M. Segovia, I. Rohouma, Q. Hong, S. Chretien and P. Clarkson, Validation of Algorithms to Estimate Distribution Network Characteristics Using Power-Hardware-in-the-Loop Configuration, Proceedings of the 2017 IEEE International Workshop on Applied Measurements for Power Systems (AMPS).

S. Chretien*, W. Sun, R. Frazer, J. Zhang, R. Hornby, P.Cooper, A. Lancaster, M. Dury (UL), Study of Gear Surface Texture Using Mallat’s Scattering Transform, AMCTM 2017, Glasgow, August 29-31 2017.

R. Garnier, C. Guyeux and S. Chrétien, Finding optimal finite biological sequences over finite alphabets: the OptiFin toolbox, IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology (IEEE CIBCB 2017), August 23-25 2017, Manchester, UK.

S. Chretien and S. Darses, An elementary approach to the problem of column selection in a rectangular matrix, The 2nd IMA Conference on the Mathematical Challenges of Big Data, Mary Ward House, London on Thursday 1st – Friday 2nd December 2016.

S. Chretien, N. Herr, J.-M. Nicod, C. Varnier - Scheduling independent parallel machines with convex programming, PGMO Days 2016, 8-9 November 2016.

S. Chretien, P. Clarkson, A. Forbes - A convex relaxation of the optimal sensor placement problem in power grids, PGMO Days 2016, 8-9 November 2016.

S. Chretien, P. Clarkson and A. Forbes, Optimal sensor placement in Smart Grids: an approach based on semi-definite relaxation and sensitivity analysis, ENBIS 2016, 11 – 15 September 2016, Sheffield, UK.

S. Chretien, P. Harris and R. Tawil, Total Variation minimization for Compressed Sensing with ``smoothly'' varying covariates, IEEE - CSE 2016, August 24-26 2016, Paris.

S. Chretien and T. Wei, The Von Neumann trace inequality for tensors, ILAS 2016, July 11-15 2016, KU Leuven, Belgium.

S. Chrétien, N. Herr, J.-M. Nicod and C. Varnier, Post-Prognostics Decision for the Commitment of Fuel Cell System, 3rd IFAC Workshop on Advanced Maintenance Engineering, Service and Technology, AMEST-16, Biarritz (France), October 19-21.

S. Chretien and T. Wei, A Lagrangian view point on robust PCA, Learning Theory, CIRM, (France), 1-6 February 2016

S. Chretien, J. Coupey, J.-M. Nicod, C. Varnier, Biosolver: a VRPTW solver for the nurses tour scheduling problem with hard time constraints, Annual workshop of the EURO working group on Vehicle Routing and Logistics optimization (VeRoLog), 6-8 Jun 2016 Nantes (France)

S. Chretien, T. Wei and B. Al-Sarray, Joint estimation and model order selection for one dimensional ARMA models via convex optimization, 8th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2015), Senate House, University of London, UK, 12-14 December 2015.

S. Chrétien and C. Guyeux, Using the Lasso for gene selection in bladder cancer data, 8th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2015), Senate House, University of London, UK, 12-14 December 2015.

S. Chrétien and T. Wei, Convex recovery of tensors using nuclear norm penalization, 12th International Conference on Latent Variable Analysis and Signal Separation, LVA 2015. LNCS, LVA-ICA 2015, E. Vincent, A. Yeredor, Z. Koldovský and P. Tichavský (editors). ArXiv.

S. Chretien, N. Herr, J.-M. Nicod, C. Varnier, A Post-Prognostics Decision Approach to Optimize the Commitment of Fuel Cell Systems in Stationary Applications, PHM 2015, Austin, TX, USA.

S. Chrétien, C. Guyeux, B. Conesa, R. Delage-Mourroux, M. Jouvenot, P. Huetz and F. Descotes, Estimating features with missing values and outliers: a Bregman-proximal point algorithm for robust Non-negative Matrix Factorization with application to gene expression analysis, LNCS ISBRA 2015, to appear. ArXiv.

S. Chrétien, Estimation of Gaussian Mixture Models via mixted nuclear/$\ell_\infty$/$\ell_1$-norm penalization, Methodological advances in Statistics related to Big Data, Castro Urdiales, june 8-12, 2015.

S. Chrétien and T. Wei, Von Neumann's trace inequality for tensors, TMA 2014, slides.

S. Chrétien, Estimation of Gaussian Mixture Models via mixted nuclear/$\ell_\infty$/$\ell_1$-norm penalization, ERCIM 2014, Pisa, 6-8 december 2014. Slides

S. Chrétien, N. Herr, J.-M. Nicod, C. Varnier, Scheduling independent parallel machines with convex programming, PGMO-COPI 2014, Ecole Polytechnique, Palaiseau, France, october 27-31 2014. Slides

S. Chrétien, Convex optimization methods for ARMA time series with trend and seasonality, Time Series Econometrics and Finance, Besancon, France, 5-6 mai 2014.

S. Chrétien, Mixture model for designs in high dimensional regression and the LASSO, European Meeting of Statisticians, Budapest, Hungary, 20-25 July 2013.

S. Chrétien, L. Toch, J.-M. Nicod, L. Philippe and V. Sonigo, Job Scheduling Using successive Linear Programming Approximations of a Sparse Model, 18th International European Conference on Parallel and Distributed Computing, Rhodes Island, Greece, August 27th-31st, 2012.

S. Chrétien, Prediction bounds for the LASSO without incoherence, 8th World Congress in Probability and Statistics, Istanbul, July 9-14, 2012.

S. Chretien and S. Darses, Sparse recovery with unknown variance: a LASSO-type approach, Imaging, Communications and Finance: Stochastic Modeling of Real-world Problems, Conference in honor of Lawrence A. Shepp, June 24-25, 2011, Columbia University, New York, NY. (Poster)

Eric Bernard, J.-M. Friedt, G. Martin, L. Moreau, D. Laffly, S. Chretien, C. Marlin, M. Griselin, Automated high resolution digital image acquisition and processing applied to polar glaciers, Polar Worlds, Paris, France, 26-28 january 2011. Abstract.

S. Chretien and J.-P. Ortega, Spectral sparsity and the modeling of high dimensional heteroscedastic phenomena, 4th CSDA International Conference on Computational and Financial Econometrics (CFE 10) Senate House, University of London, UK 10-12 December 2010.

S. Chretien, l1-penalized maximum likelihood estimation for sparse polytomic regression models, EMS 2010, August 17-22, University of Piraeus.

S. Chretien, Lagrangian relaxation for the Compressed Sensing problem, SMAI 09, Mai 2009, La Colle sur Loup. Slides

S. Chretien, The two-stage l1 relaxation for the Compressed Sensing problem, SPARS 09, April 2009, Saint Malo. (Poster)

S. Chretien and J.-P. Ortega, Decay of correlation for a discretized differential delay equation, BIRS 07w5068 Geometric Mechanics: Continuous and discrete, finite and infinite dimensional, Auguts 2007, Banff.

S. Chretien, Tighter relaxations for the sparsest recovery problem, ICIAM 07, Zurich. Slides Proceedings (non free)

S. Chretien and J.-P. Ortega, Decay of correlation for a discretized differential delay equation, IMWSM 2007, Sevilla. Slides .

S. Chretien, Relaxed MCMC for random fields with quadratic Hamiltonians over binaries. 25 th European Meeting of Statisticians, Oslo, 2005. Slides.

S. Chretien and F. Corset, Une borne inferieure pour les temps d'inspection en maintenance. Journees de la Societe Francaise de Statistiques 2005.

S. Chretien and F. Corset, A lower bound on inspection time for complex systems with Weibull transitions. COMPSTAT 2004 (Prague), 799--806, Physica, Heidelberg, 2004. Proceedings (non free).(Poster)

S. Chretien and F. Corset, A lower bound on inspection time for complex systems with Weibull transitions. MMR 2004.

S. Chretien and F. Corset, Reconstruction d'images binaires par estimation moindres carres et optimisation de valeur propre. Journees de la Societe Francaise de Statistiques 2004.

S. Chretien and F. Corset, Least squares reconstruction of binary images using eigenvalue optimization. COMPSTAT 2002 (Berlin), 419--424, Physica, Heidelberg, 2002. Proceedings (non free).

C. Biernacki and S. Chretien, Degeneracy in the likelihood approach to univariate gaussian mixture estimation with EM. ASMDA 2001 (Compiegne), 206--212, 2001. Proceedings (free access).

S. Chretien, EM-type algorithm for maximum likelihood estimation and application to medical imaging, (Invited Speaker), journees de la Societe Francaise de Statistiques, Fes, Maroc, May 2000. Abstract , Slides.

S. Chretien, A.O. Hero and R. Piramuthu, Statistical Proximal Point Methods for Image Reconstruction, SIAM Annual Meeting, Puerto Rico, 10--14 juillet 2000. Link, Abstract , Slides.

S. Chretien, Generalized proximal point algorithms and bundle implementation, Conference groupe MODE de la SMAI, Orleans, France, mars 1999, Link .

S. Chretien and A. O. Hero, Acceleration of the EM algorithm via proximal point iterations, IEEE International Symposium on Information Theory, Boston, August 1998. Paper (non free).

S. Chretien and I. Dologlou, Successive projection-like algorithms for signal approximation/zero error modelling, Proc. IEEE international conference on acoustics, speech and signal processing, Detroit, USA, (1995), 1240-1243. Paper (non free)

S. Chretien and I. Dologlou, Image compression based on reduced rank approximation and adaptive error modelling, Proc. European Signal Processing Conference, Edinburgh, UK, (1994), 592-595.