Eric Moulines

Orcid: 0000-0002-2058-0693

According to our database1, Eric Moulines authored at least 247 papers between 1987 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Rates of convergence for density estimation with generative adversarial networks.
J. Mach. Learn. Res., 2024

Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents.
CoRR, 2024

Joint Channel Selection using FedDRL in V2X.
CoRR, 2024

Optimal Design for Reward Modeling in RLHF.
CoRR, 2024

Variational Diffusion Posterior Sampling with Midpoint Guidance.
CoRR, 2024

Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation.
CoRR, 2024

A New Bound on the Cumulant Generating Function of Dirichlet Processes.
CoRR, 2024

Piecewise deterministic generative models.
CoRR, 2024

Unravelling in Collaborative Learning.
CoRR, 2024

Conditionally valid Probabilistic Conformal Prediction.
CoRR, 2024

Mitigating Externalities while Learning: an Online Version of the Coase Theorem.
CoRR, 2024

Central Limit Theorem for Bayesian Neural Network trained with Variational Inference.
CoRR, 2024

Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning.
CoRR, 2024

ReALLM: A general framework for LLM compression and fine-tuning.
CoRR, 2024

Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors.
CoRR, 2024

SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.
CoRR, 2024

Bayesian ECG reconstruction using denoising diffusion generative models.
CoRR, 2024

Object Detection Models Sensitivity & Robustness to Satellite-based Adversarial Attacks.
Proceedings of the IGARSS 2024, 2024

Incentivized Learning in Principal-Agent Bandit Games.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Demonstration-Regularized RL.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Deep Reinforcement Learning Algorithms for Hybrid V2X Communication: A Benchmarking Study.
Proceedings of the IEEE International Conference on Communications Workshops, 2024

FAVANO: Federated Averaging with Asynchronous Nodes.
Proceedings of the IEEE International Conference on Acoustics, 2024

Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Efficient Conformal Prediction under Data Heterogeneity.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Queuing dynamics of asynchronous Federated Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Stochastic variable metric proximal gradient with variance reduction for non-convex composite optimization.
Stat. Comput., June, 2023

Unifying mirror descent and dual averaging.
Math. Program., May, 2023

Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning.
IEEE Trans. Signal Process., 2023

One-Step Distributional Reinforcement Learning.
Trans. Mach. Learn. Res., 2023

Finite-Sample Analysis of the Temporal Difference Learning.
CoRR, 2023

Deep Reinforcement Learning Algorithms for Hybrid V2X Communication: A Benchmarking Study.
CoRR, 2023

Monte Carlo guided Diffusion for Bayesian linear inverse problems.
CoRR, 2023

Balanced Training of Energy-Based Models with Adaptive Flow Sampling.
CoRR, 2023

FAVAS: Federated AVeraging with ASynchronous clients.
CoRR, 2023

Model-free Posterior Sampling via Learning Rate Randomization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Oil and Gas Automatic Infrastructure Mapping: Leveraging High-Resolution Satellite Imagery Through Fine-Tuning of Object Detection Models.
Proceedings of the Neural Information Processing - 30th International Conference, 2023

Fast Rates for Maximum Entropy Exploration.
Proceedings of the International Conference on Machine Learning, 2023

Conformal Prediction for Federated Uncertainty Quantification Under Label Shift.
Proceedings of the International Conference on Machine Learning, 2023

Quantile Credit Assignment.
Proceedings of the International Conference on Machine Learning, 2023

On Sampling with Approximate Transport Maps.
Proceedings of the International Conference on Machine Learning, 2023

State and parameter learning with PARIS particle Gibbs.
Proceedings of the International Conference on Machine Learning, 2023

Federated Boolean Neural Networks Learning.
Proceedings of the Eighth International Conference on Fog and Mobile Edge Computing, 2023

Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Law of Large Numbers for Bayesian two-layer Neural Network trained with Variational Inference.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes.
Proceedings of the Conference on Lifelong Learning Agents, 2023

Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

ASkewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
A Proximal Markov Chain Monte Carlo Method for Bayesian Inference in Imaging Inverse Problems: When Langevin Meets Moreau.
SIAM Rev., 2022

Variance reduction for additive functionals of Markov chains via martingale representations.
Stat. Comput., 2022

Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation.
CoRR, 2022

Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study.
CoRR, 2022

On the geometric convergence for MALA under verifiable conditions.
CoRR, 2022

Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Local-Global MCMC kernels: the best of both worlds.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

FedPop: A Bayesian Approach for Personalised Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

BR-SNIS: Bias Reduced Self-Normalized Importance Sampling.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses.
Proceedings of the International Conference on Machine Learning, 2022

Diffusion bridges vector quantized variational autoencoders.
Proceedings of the International Conference on Machine Learning, 2022

A Patient-Specific Single Equivalent Dipole Model.
Proceedings of the Computing in Cardiology, 2022

Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex Problems.
Proceedings of the International Conference on Algorithmic Learning Theory, 29 March, 2022

QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
On Stochastic Gradient Langevin Dynamics with Dependent Data Streams: The Fully Nonconvex Case.
SIAM J. Math. Data Sci., 2021

Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence.
Stat. Comput., 2021

Variance Reduction for Dependent Sequences with Applications to Stochastic Gradient MCMC.
SIAM/ASA J. Uncertain. Quantification, 2021

Ex<sup>2</sup>MCMC: Sampling through Exploration Exploitation.
CoRR, 2021

Federated Expectation Maximization with heterogeneity mitigation and variance reduction.
CoRR, 2021

Uniform minorization condition and convergence bounds for discretizations of kinetic Langevin dynamics.
CoRR, 2021

DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm.
CoRR, 2021

Model-free policy evaluation in Reinforcement Learning via upper solutions.
CoRR, 2021

The Perturbed Prox-Preconditioned Spider Algorithm for EM-Based Large Scale Learning.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2021

The Perturbed Prox-Preconditioned Spider Algorithm: Non-Asymptotic Convergence Bounds.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2021

NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Federated-EM with heterogeneity mitigation and variance reduction.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Monte Carlo Variational Auto-Encoders.
Proceedings of the 38th International Conference on Machine Learning, 2021

DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs.
Proceedings of the 38th International Conference on Machine Learning, 2021

Counterfactual Credit Assignment in Model-Free Reinforcement Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Geom-Spider-EM: Faster Variance Reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization.
Proceedings of the IEEE International Conference on Acoustics, 2021

On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning.
Proceedings of the Conference on Learning Theory, 2021

On Riemannian Stochastic Approximation Schemes with Fixed Step-Size.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
On Stability of a Class of Filters for Nonlinear Stochastic Systems.
SIAM J. Control. Optim., 2020

Variance reduction for Markov chains with application to MCMC.
Stat. Comput., 2020

f-SAEM: A fast stochastic approximation of the EM algorithm for nonlinear mixed effects models.
Comput. Stat. Data Anal., 2020

A Stochastic Path-Integrated Differential EstimatoR Expectation Maximization Algorithm.
CoRR, 2020

Convergence Analysis of Riemannian Stochastic Approximation Schemes.
CoRR, 2020

MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference.
CoRR, 2020

On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation.
CoRR, 2020

A Stochastic Path Integral Differential EstimatoR Expectation Maximization Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations.
Proceedings of the 37th International Conference on Machine Learning, 2020

Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise.
Proceedings of the Conference on Learning Theory, 2020

2019
Low-rank model with covariates for count data with missing values.
J. Multivar. Anal., 2019

On the Global Convergence of (Fast) Incremental Expectation Maximization Methods.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Non-asymptotic Analysis of Biased Stochastic Approximation Scheme.
Proceedings of the Conference on Learning Theory, 2019

2018
Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau.
SIAM J. Imaging Sci., 2018

MONK - Outlier-Robust Mean Embedding Estimation by Median-of-Means.
CoRR, 2018

Stochastic Fista Algorithms: So Fast ?
Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

The promises and pitfalls of Stochastic Gradient Langevin Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Optimizing Thermal Comfort and Energy Consumption in a Large Building without Renovation Work.
Proceedings of the 2018 IEEE Data Science Workshop, 2018

Bounds on the Covariance Matrix of a Class of Kalman-Bucy Filters for Systems with Non-Linear Dynamics.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017
Fixed Rank Kriging for Cellular Coverage Analysis.
IEEE Trans. Veh. Technol., 2017

Decentralized Frank-Wolfe Algorithm for Convex and Nonconvex Problems.
IEEE Trans. Autom. Control., 2017

MCMC design-based non-parametric regression for rare event. Application to nested risk computations.
Monte Carlo Methods Appl., 2017

On Perturbed Proximal Gradient Algorithms.
J. Mach. Learn. Res., 2017

Optimal scaling of the random walk Metropolis algorithm under L p mean differentiability.
J. Appl. Probab., 2017

Particle rejuvenation of Rao-Blackwellized sequential Monte Carlo smoothers for conditionally linear and Gaussian models.
EURASIP J. Adv. Signal Process., 2017

Online EM for functional data.
Comput. Stat. Data Anal., 2017

Fast and privacy preserving distributed low-rank regression.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Parallelized Stochastic Gradient Markov Chain Monte Carlo algorithms for non-negative matrix factorization.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
Spatial Prediction Under Location Uncertainty in Cellular Networks.
IEEE Trans. Wirel. Commun., 2016

Sequential Design of Computer Experiments for the Assessment of Fetus Exposure to Electromagnetic Fields.
Technometrics, 2016

Convergence of Markovian Stochastic Approximation with Discontinuous Dynamics.
SIAM J. Control. Optim., 2016

A Shrinkage-Thresholding Metropolis Adjusted Langevin Algorithm for Bayesian Variable Selection.
IEEE J. Sel. Top. Signal Process., 2016

Decentralized Projection-free Optimization for Convex and Non-convex Problems.
CoRR, 2016

Considering spatial information to improve anomaly detection in heterogeneous hyperspectral images.
Proceedings of the 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2016

Nonparametric estimation of a shot-noise process.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

On the LP-convergence of a Girsanov theorem based particle filter.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

D-FW: Communication efficient distributed algorithms for high-dimensional sparse optimization.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

A projection-free decentralized algorithm for non-convex optimization.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Maximum likelihood estimation of a low-order building model.
Proceedings of the 24th European Signal Processing Conference, 2016

2015
On parallel implementation of sequential Monte Carlo methods: the island particle model.
Stat. Comput., 2015

Quantitative bounds of convergence for geometrically ergodic Markov chain in the Wasserstein distance with application to the Metropolis Adjusted Langevin Algorithm.
Stat. Comput., 2015

Convergence Analysis of a Stochastic Projection-free Algorithm.
CoRR, 2015

The sexy job in the next ten years will be statisticians.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

Centralized self-optimization of interference management in LTE-A HetNets.
Proceedings of the Design and Deployment of Small Cell Networks, 2015

2014
Adaptive sequential Monte Carlo by means of mixture of experts.
Stat. Comput., 2014

Low complexity spatial interpolation for cellular coverage analysis.
Proceedings of the 12th International Symposium on Modeling and Optimization in Mobile, 2014

Active antenna systems for centralized self-optimization of capacity in LTE-A.
Proceedings of the 2014 IEEE Wireless Communications and Networking Conference Workshops, 2014

Coverage mapping using spatial interpolation with field measurements.
Proceedings of the 25th IEEE Annual International Symposium on Personal, 2014

Probabilistic low-rank matrix completion on finite alphabets.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Adaptive Equi-Energy Sampler: Convergence and Illustration.
ACM Trans. Model. Comput. Simul., 2013

Kernel-Based Methods for Hypothesis Testing: A Unified View.
IEEE Signal Process. Mag., 2013

Aircraft classification with a low resolution infrared sensor.
Mach. Vis. Appl., 2013

Centralized self-optimization in LTE-A using Active Antenna Systems.
Proceedings of the IFIP Wireless Days, 2013

Surrogate Based Centralized Automated Optimization Applied to LTE Mobility Load Balancing.
Proceedings of the 78th IEEE Vehicular Technology Conference, 2013

Surrogate Based Centralized SON: Application to Interference Mitigation in LTE-A HetNets.
Proceedings of the 77th IEEE Vehicular Technology Conference, 2013

Centralized self-optimization of pilot powers for load balancing in LTE.
Proceedings of the 24th IEEE Annual International Symposium on Personal, 2013

Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n).
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012
Detecting Aircraft With a Low-Resolution Infrared Sensor.
IEEE Trans. Image Process., 2012

Improving coverage estimation for cellular networks with spatial bayesian prediction based on measurements.
Proceedings of the 2012 ACM SIGCOMM workshop on Cellular networks: operations, 2012

An online learning algorithm for mixture models of deformable templates.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

New Online EM Algorithms for General Hidden Markov Models. Application to the SLAM Problem.
Proceedings of the Latent Variable Analysis and Signal Separation, 2012

Sequential design of computer experiments for parameter estimation with application to numerical dosimetry.
Proceedings of the 20th European Signal Processing Conference, 2012

2011
Inference of a Generalized Long Memory Process in the Wavelet Domain.
IEEE Trans. Signal Process., 2011

Error Exponents for Neyman-Pearson Detection of a Continuous-Time Gaussian Markov Process From Regular or Irregular Samples.
IEEE Trans. Inf. Theory, 2011

On adaptive stratification.
Ann. Oper. Res., 2011

Best Sensor Selection for an Iterative REM Construction.
Proceedings of the 74th IEEE Vehicular Technology Conference, 2011

Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

CLT for eigen-inference methods in cognitive radios.
Proceedings of the IEEE International Conference on Acoustics, 2011

An algorithm for fast REM construction.
Proceedings of the 6th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications, 2011

On Upper-Confidence Bound Policies for Switching Bandit Problems.
Proceedings of the Algorithmic Learning Theory - 22nd International Conference, 2011

2010
The expectation and sparse maximization algorithm.
J. Commun. Networks, 2010

High-Rate Quantization for the Neyman-Pearson Detection of Hidden Markov Processes
CoRR, 2010

Detecting aircraft with a low resolution infrared sensor.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2010

Maximum likelihood blind deconvolution for sparse systems.
Proceedings of the 2nd International Workshop on Cognitive Information Processing, 2010

2009
On approximate maximum-likelihood methods for blind identification: how to cope with the curse of dimensionality.
IEEE Trans. Signal Process., 2009

Error exponents for Neyman-Pearson detection of a continuous-time Gaussian Markov process from noisy irregular samples
CoRR, 2009

On the error exponents for detecting randomly sampled noisy diffusion processes.
Proceedings of the IEEE International Conference on Acoustics, 2009

2008
Adaptive methods for sequential importance sampling with application to state space models.
Stat. Comput., 2008

Opportunistic Spectrum Access with IEEE 802.11 in IEEE P1900.4 Framework.
Proceedings of the IEEE International Conference on Wireless and Mobile Computing, 2008

Semi Dynamic Parameter Tuning for Optimized Opportunistic Spectrum Access.
Proceedings of the 68th IEEE Vehicular Technology Conference, 2008

Informed spectrum usage in cognitive radio networks: Interference cartography.
Proceedings of the IEEE 19th International Symposium on Personal, 2008

Kernel Change-point Analysis.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Opportunistic Spectrum Access: Online Search of Optimality.
Proceedings of the Global Communications Conference, 2008. GLOBECOM 2008, New Orleans, LA, USA, 30 November, 2008

A Near Optimal Policy for Channel Allocation in Cognitive Radio.
Proceedings of the Recent Advances in Reinforcement Learning, 8th European Workshop, 2008

2007
Statistical Pileup Correction Method for HPGe Detectors.
IEEE Trans. Signal Process., 2007

An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo.
Proc. IEEE, 2007

Optimization of Radio Measurements Exploitation in Wireless Mobile Networks.
J. Commun., 2007

Online EM Algorithm for Latent Data Models
CoRR, 2007

Testing for Homogeneity with Kernel Fisher Discriminant Analysis.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

A New Approach for Mobile Localization in Multipath Scenarios.
Proceedings of IEEE International Conference on Communications, 2007

2006
ODE methods for Markov chain stability with applications to MCMC.
Proceedings of the 1st International Conference on Performance Evaluation Methodolgies and Tools, 2006

Energy Spectrum Reconstruction for HPGe Detectors Using Analytical Pile-Up Correction.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Source Localization from Quantized Time of Arrival Measurements.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Recursive Em Algorithm with Applications to Doa Estimation.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

2005
Stability of Stochastic Approximation under Verifiable Conditions.
SIAM J. Control. Optim., 2005

Classification et sélection de caractéristiques de textures. Utilisation d'algorithmes automatiques supervisés de sélection d'attributs pour la classification d'images.
Rev. d'Intelligence Artif., 2005

Comparison of Resampling Schemes for Particle Filtering
CoRR, 2005

Modeling, identification, and control of large-scale dynamical systems.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

On the use of particle filtering for maximum likelihood parameter estimation.
Proceedings of the 13th European Signal Processing Conference, 2005

Méthodologie de sélection de caractéristiques pour la classification d'images satellitaires.
Proceedings of the Actes de CAP 05, Conférence francophone sur l'apprentissage automatique, 2005

Inference in hidden Markov models.
Springer series in statistics, Springer, ISBN: 978-0-387-40264-2, 2005

2004
Global Sampling for Sequential Filtering over Discrete State Space.
EURASIP J. Adv. Signal Process., 2004

2003
A semi-blind channel estimation technique based on second-order blind method for CDMA systems.
IEEE Trans. Signal Process., 2003

2002
Long-range dependence and heavy-tail modeling for teletraffic data.
IEEE Signal Process. Mag., 2002

Semidefinite positive relaxation of the maximum-likelihood criterion applied to multiuser detection in a CDMA context.
IEEE Signal Process. Lett., 2002

2001
Blind identification of multipath channels: a parametric subspace approach.
IEEE Trans. Signal Process., 2001

Estimation of the spectral envelope of voiced sounds using a penalized likelihood approach.
IEEE Trans. Speech Audio Process., 2001

Training-based channel estimation and de-noising for the UMTS TDD mode.
Proceedings of the 54th IEEE Vehicular Technology Conference, 2001

An adaptive broadband estimator of the fractional differencing coefficient.
Proceedings of the IEEE International Conference on Acoustics, 2001

2000
On blind multiuser forward link channel estimation by the subspace method: identifiability results.
IEEE Trans. Signal Process., 2000

In-variance of subspace based estimators.
IEEE Trans. Signal Process., 2000

On the performance of semi-blind subspace-based channel estimation.
IEEE Trans. Signal Process., 2000

On a Perturbation Approach for the Analysis of Stochastic Tracking Algorithms.
SIAM J. Control. Optim., 2000

Performance of a subspace based semi-blind technique in the UMTS TDD mode context.
Proceedings of the IEEE International Conference on Acoustics, 2000

1999
Simulation-based methods for blind maximum-likelihood filter identification.
Signal Process., 1999

A parametric blind subspace identification: robustness issue.
IEEE Commun. Lett., 1999

Blind knowledge based algorithms based on second order statistics.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

Application of blind second order statistics MIMO identification methods to the blind CDMA forward link channel estimation.
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999

1998
Continuous probabilistic transform for voice conversion.
IEEE Trans. Speech Audio Process., 1998

An algorithm for maximum likelihood estimation of hidden Markov models with unknown state-tying.
IEEE Trans. Speech Audio Process., 1998

Blind and semi-blind equalization: methods and algorithms.
Ann. des Télécommunications, 1998

Polynomial quasi-harmonic models for speech analysis and synthesis.
Proceedings of the 1998 IEEE International Conference on Acoustics, 1998

Quasi-Newton method for maximum likelihood estimation of hidden Markov models.
Proceedings of the 1998 IEEE International Conference on Acoustics, 1998

On the Convergence of Iterated Random Maps with Applications to the MCEM Algorithm.
Proceedings of the COMPSTAT 1998, 1998

Bayesian Analysis of Overdispersed Count Data with Application to Teletraffic Monitoring.
Proceedings of the COMPSTAT 1998, 1998

A locally stationary semi-Markovian representation for ethernet LAN traffic data.
Proceedings of the Broadband Communications: The future of telecommunications, 1998

1997
A blind source separation technique using second-order statistics.
IEEE Trans. Signal Process., 1997

Prediction error method for second-order blind identification.
IEEE Trans. Signal Process., 1997

On subspace methods for blind identification of single-input multiple-output FIR systems.
IEEE Trans. Signal Process., 1997

A subspace algorithm for certain blind identification problems.
IEEE Trans. Inf. Theory, 1997

Subspace method for blind identification of multichannel FIR systems in noise field with unknown spatial covariance.
IEEE Signal Process. Lett., 1997

A simulated annealing version of the EM algorithm for non-Gaussian deconvolution.
Stat. Comput., 1997

Asymptotically invariant Gaussianity test for causal invertible time series.
Proceedings of the 1997 IEEE International Conference on Acoustics, 1997

Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models.
Proceedings of the 1997 IEEE International Conference on Acoustics, 1997

1996
Time-domain procedures for testing that a stationary time-series is Gaussian.
IEEE Trans. Signal Process., 1996

Regularization techniques for discrete cepstrum estimation.
IEEE Signal Process. Lett., 1996

Subspace methods for blind identification of SIMO-FIR systems.
Proceedings of the 1996 IEEE International Conference on Acoustics, 1996

Second order blind equalization in multiple input multiple output FIR systems: a weighted least squares approach.
Proceedings of the 1996 IEEE International Conference on Acoustics, 1996

1995
Subspace methods for the blind identification of multichannel FIR filters.
IEEE Trans. Signal Process., 1995

The generalized multidelay adaptive filter: structure and convergence analysis.
IEEE Trans. Signal Process., 1995

Asymptotic performance analysis of direction-finding algorithms based on fourth-order cumulants.
IEEE Trans. Signal Process., 1995

Editorial.
Speech Commun., 1995

Non-parametric techniques for pitch-scale and time-scale modification of speech.
Speech Commun., 1995

High-quality speech modification based on a harmonic + noise model.
Proceedings of the Fourth European Conference on Speech Communication and Technology, 1995

Statistical methods for voice quality transformation.
Proceedings of the Fourth European Conference on Speech Communication and Technology, 1995

Prediction error methods for time-domain blind identification of multichannel FIR filters.
Proceedings of the 1995 International Conference on Acoustics, 1995

1994
A robustness property of DOA estimators based on covariance.
IEEE Trans. Signal Process., 1994

Asymptotic performance of second order blind separation.
Proceedings of ICASSP '94: IEEE International Conference on Acoustics, 1994

1993
HNS: Speech modification based on a harmonic+noise model.
Proceedings of the IEEE International Conference on Acoustics, 1993

Minimum constrast estimation with applications to array processing.
Proceedings of the IEEE International Conference on Acoustics, 1993

1992
Voice transformation using PSOLA technique.
Speech Commun., 1992

Direction finding algorithms using fourth order statistics: asymptotic performance analysis.
Proceedings of the 1992 IEEE International Conference on Acoustics, 1992

Low-delay frequency domain LMS algorithm.
Proceedings of the 1992 IEEE International Conference on Acoustics, 1992

1991
Voice tranformation using PSOLA technique.
Proceedings of the Second European Conference on Speech Communication and Technology, 1991

1990
Detection of the glottal closure by jumps in the statistical properties of the speech signal.
Speech Commun., 1990

Pitch-synchronous waveform processing techniques for text-to-speech synthesis using diphones.
Speech Commun., 1990

A real-time French text-to-speech system generating high-quality synthetic speech.
Proceedings of the 1990 International Conference on Acoustics, 1990

1989
Detection of the glottal closure by jumps in the statistical properties of the signal.
Proceedings of the First European Conference on Speech Communication and Technology, 1989

A diphone synthesis system based on time-domain prosodic modifications of speech.
Proceedings of the IEEE International Conference on Acoustics, 1989

1988
Text-to-speech algorithms based on FFT synthesis.
Proceedings of the IEEE International Conference on Acoustics, 1988

1987
Text-to-speech synthesis in the French electronic mail environment.
Proceedings of the European Conference on Speech Technology, 1987


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