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2020 – today
- 2024
[j76]Nikita Puchkin, Sergey Samsonov, Denis Belomestny, Eric Moulines, Alexey Naumov:
Rates of convergence for density estimation with generative adversarial networks. J. Mach. Learn. Res. 25: 29:1-29:47 (2024)- [c135]Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines:
Queuing dynamics of asynchronous Federated Learning. AISTATS 2024: 1711-1719 - [c134]Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov:
Efficient Conformal Prediction under Data Heterogeneity. AISTATS 2024: 4879-4887 - [c133]Sergey Samsonov, Daniil Tiapkin, Alexey Naumov, Eric Moulines:
Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability. COLT 2024: 4511-4547 - [c132]Louis Leconte, Van Minh Nguyen, Eric Moulines:
FAVANO: Federated Averaging with Asynchronous Nodes. ICASSP 2024: 5665-5669 - [c131]Fouzi Boukhalfa, Réda Alami, Mastane Achab, Eric Moulines, Mehdi Bennis, Thierry Lestable:
Deep Reinforcement Learning Algorithms for Hybrid V2X Communication: A Benchmarking Study. ICC Workshops 2024: 1956-1961 - [c130]Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff, Eric Moulines:
Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems. ICLR 2024 - [c129]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard:
Demonstration-Regularized RL. ICLR 2024 - [c128]Tom Huix, Anna Korba, Alain Oliviero Durmus, Eric Moulines:
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians. ICML 2024 - [c127]Antoine Scheid, Daniil Tiapkin, Etienne Boursier, Aymeric Capitaine, Eric Moulines, Michael I. Jordan, El-Mahdi El-Mhamdi, Alain Oliviero Durmus:
Incentivized Learning in Principal-Agent Bandit Games. ICML 2024 - [c126]Jade Eva Guisiano, Domenico Barretta, Éric Moulines, Thomas Lauvaux, Jérémie Sublime:
Object Detection Models Sensitivity & Robustness to Satellite-based Adversarial Attacks. IGARSS 2024: 7844-7848 - [i72]Gabriel Victorino Cardoso, Lisa Bedin, Josselin Duchateau, Rémi Dubois, Eric Moulines:
Bayesian ECG reconstruction using denoising diffusion generative models. CoRR abs/2401.05388 (2024) - [i71]Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Réda Alami, Alexey Naumov, Eric Moulines:
SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning. CoRR abs/2402.04114 (2024) - [i70]Antoine Scheid, Daniil Tiapkin, Etienne Boursier, Aymeric Capitaine, El Mahdi El Mhamdi, Eric Moulines, Michael I. Jordan, Alain Durmus:
Incentivized Learning in Principal-Agent Bandit Games. CoRR abs/2403.03811 (2024) - [i69]Yazid Janati El Idrissi, Alain Durmus, Eric Moulines, Jimmy Olsson:
Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors. CoRR abs/2403.11407 (2024) - [i68]Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines:
Queuing dynamics of asynchronous Federated Learning. CoRR abs/2405.00017 (2024) - [i67]Louis Leconte, Lisa Bedin, Van Minh Nguyen, Eric Moulines:
ReALLM: A general framework for LLM compression and fine-tuning. CoRR abs/2405.13155 (2024) - [i66]Sergey Samsonov, Eric Moulines, Qi-Man Shao, Zhuo-Song Zhang, Alexey Naumov:
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning. CoRR abs/2405.16644 (2024) - [i65]Tom Huix, Anna Korba, Alain Durmus, Eric Moulines:
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians. CoRR abs/2406.04012 (2024) - [i64]Arnaud Descours, Tom Huix, Arnaud Guillin, Manon Michel, Éric Moulines, Boris Nectoux:
Central Limit Theorem for Bayesian Neural Network trained with Variational Inference. CoRR abs/2406.09048 (2024) - [i63]Antoine Scheid, Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael I. Jordan, Alain Durmus:
Mitigating Externalities while Learning: an Online Version of the Coase Theorem. CoRR abs/2406.19824 (2024) - [i62]Vincent Plassier, Alexander Fishkov, Maxim Panov, Eric Moulines:
Conditionally valid Probabilistic Conformal Prediction. CoRR abs/2407.01794 (2024) - [i61]Aymeric Capitaine, Etienne Boursier, Antoine Scheid, Eric Moulines, Michael I. Jordan, El-Mahdi El-Mhamdi, Alain Durmus:
Unravelling in Collaborative Learning. CoRR abs/2407.14332 (2024) - [i60]Andrea Bertazzi, Alain Oliviero Durmus, Dario Shariatian, Umut Simsekli, Eric Moulines:
Piecewise deterministic generative models. CoRR abs/2407.19448 (2024) - [i59]Pierre Perrault, Denis Belomestny, Pierre Ménard, Éric Moulines, Alexey Naumov, Daniil Tiapkin, Michal Valko:
A New Bound on the Cumulant Generating Function of Dirichlet Processes. CoRR abs/2409.18621 (2024) - 2023
- [j75]Anatoli B. Juditsky, Joon Kwon
, Éric Moulines:
Unifying mirror descent and dual averaging. Math. Program. 199(1): 793-830 (2023) - [j74]Gersende Fort, Eric Moulines:
Stochastic variable metric proximal gradient with variance reduction for non-convex composite optimization. Stat. Comput. 33(3): 65 (2023) - [j73]Mastane Achab, Réda Alami, Yasser Abdelaziz Dahou Djilali, Kirill Fedyanin, Eric Moulines:
One-Step Distributional Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j72]Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Hoi-To Wai:
Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning. IEEE Trans. Signal Process. 71: 3117-3148 (2023) - [c125]Louis Leconte, Sholom Schechtman, Eric Moulines:
ASkewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks. AISTATS 2023: 3644-3663 - [c124]Vincent Plassier, Eric Moulines, Alain Durmus:
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms. AISTATS 2023: 5299-5356 - [c123]Réda Alami, Mohammed Mahfoud, Eric Moulines:
Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes. CoLLAs 2023: 715-744 - [c122]Sholom Schechtman, Daniil Tiapkin, Michael Muehlebach, Éric Moulines:
Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold. COLT 2023: 1228-1258 - [c121]Arnaud Descours, Tom Huix, Arnaud Guillin, Manon Michel, Éric Moulines, Boris Nectoux:
Law of Large Numbers for Bayesian two-layer Neural Network trained with Variational Inference. COLT 2023: 4657-4695 - [c120]Louis Leconte, Van Minh Nguyen, Eric Moulines:
Federated Boolean Neural Networks Learning. FMEC 2023: 247-253 - [c119]Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff, Eric Moulines, Jimmy Olsson:
State and parameter learning with PARIS particle Gibbs. ICML 2023: 3625-3675 - [c118]Louis Grenioux, Alain Oliviero Durmus, Eric Moulines, Marylou Gabrié:
On Sampling with Approximate Transport Maps. ICML 2023: 11698-11733 - [c117]Thomas Mesnard, Wenqi Chen, Alaa Saade, Yunhao Tang, Mark Rowland, Theophane Weber, Clare Lyle, Audrunas Gruslys, Michal Valko, Will Dabney, Georg Ostrovski, Eric Moulines, Rémi Munos:
Quantile Credit Assignment. ICML 2023: 24517-24531 - [c116]Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov:
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. ICML 2023: 27907-27947 - [c115]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Ménard:
Fast Rates for Maximum Entropy Exploration. ICML 2023: 34161-34221 - [c114]Jade Eva Guisiano, Éric Moulines, Thomas Lauvaux, Jérémie Sublime:
Oil and Gas Automatic Infrastructure Mapping: Leveraging High-Resolution Satellite Imagery Through Fine-Tuning of Object Detection Models. ICONIP (12) 2023: 442-458 - [c113]Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander V. Gasnikov, Alexey Naumov, Eric Moulines:
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities. NeurIPS 2023 - [c112]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard:
Model-free Posterior Sampling via Learning Rate Randomization. NeurIPS 2023 - [i58]Gersende Fort, Eric Moulines:
Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization. CoRR abs/2301.00631 (2023) - [i57]Louis Grenioux, Alain Durmus, Éric Moulines, Marylou Gabrié:
On Sampling with Approximate Transport Maps. CoRR abs/2302.04763 (2023) - [i56]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Ménard:
Fast Rates for Maximum Entropy Exploration. CoRR abs/2303.08059 (2023) - [i55]Réda Alami, Mohammed Mahfoud, Eric Moulines:
Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes. CoRR abs/2304.00232 (2023) - [i54]Mastane Achab, Réda Alami, Yasser Abdelaziz Dahou Djilali, Kirill Fedyanin, Eric Moulines:
One-Step Distributional Reinforcement Learning. CoRR abs/2304.14421 (2023) - [i53]Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander V. Gasnikov, Alexey Naumov, Eric Moulines:
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities. CoRR abs/2305.15938 (2023) - [i52]Louis Leconte, Van Minh Nguyen, Eric Moulines:
FAVAS: Federated AVeraging with ASynchronous clients. CoRR abs/2305.16099 (2023) - [i51]Louis Grenioux, Éric Moulines, Marylou Gabrié:
Balanced Training of Energy-Based Models with Adaptive Flow Sampling. CoRR abs/2306.00684 (2023) - [i50]Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov:
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. CoRR abs/2306.05131 (2023) - [i49]Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff, Eric Moulines:
Monte Carlo guided Diffusion for Bayesian linear inverse problems. CoRR abs/2308.07983 (2023) - [i48]Fouzi Boukhalfa, Réda Alami, Mastane Achab, Eric Moulines, Mehdi Bennis:
Deep Reinforcement Learning Algorithms for Hybrid V2X Communication: A Benchmarking Study. CoRR abs/2310.03767 (2023) - [i47]Sergey Samsonov, Daniil Tiapkin, Alexey Naumov, Eric Moulines:
Finite-Sample Analysis of the Temporal Difference Learning. CoRR abs/2310.14286 (2023) - [i46]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard:
Demonstration-Regularized RL. CoRR abs/2310.17303 (2023) - [i45]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard:
Model-free Posterior Sampling via Learning Rate Randomization. CoRR abs/2310.18186 (2023) - [i44]Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov:
Efficient Conformal Prediction under Data Heterogeneity. CoRR abs/2312.15799 (2023) - 2022
- [j71]Denis Belomestny, Eric Moulines, Sergey Samsonov:
Variance reduction for additive functionals of Markov chains via martingale representations. Stat. Comput. 32(1): 16 (2022) - [j70]Alain Durmus, Éric Moulines, Marcelo Pereyra:
A Proximal Markov Chain Monte Carlo Method for Bayesian Inference in Imaging Inverse Problems: When Langevin Meets Moreau. SIAM Rev. 64(4): 991-1028 (2022) - [c111]Maxime Vono, Vincent Plassier, Alain Durmus, Aymeric Dieuleveut, Eric Moulines:
QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning. AISTATS 2022: 6459-6500 - [c110]Belhal Karimi, Hoi-To Wai, Eric Moulines, Ping Li:
Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex Problems. ALT 2022: 606-637 - [c109]Gabriel Cardoso, Geneviève Robin, Andony Arrieula, Mark Potse, Michel Haïssaguerre, Eric Moulines, Rémi Dubois:
A Patient-Specific Single Equivalent Dipole Model. CinC 2022: 1-4 - [c108]Max Cohen, Guillaume Quispe, Sylvain Le Corff, Charles Ollion, Eric Moulines:
Diffusion bridges vector quantized variational autoencoders. ICML 2022: 4141-4156 - [c107]Daniil Tiapkin, Denis Belomestny, Eric Moulines, Alexey Naumov, Sergey Samsonov, Yunhao Tang, Michal Valko, Pierre Ménard:
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses. ICML 2022: 21380-21431 - [c106]Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson:
BR-SNIS: Bias Reduced Self-Normalized Importance Sampling. NeurIPS 2022 - [c105]Nikita Kotelevskii, Maxime Vono, Alain Durmus, Eric Moulines:
FedPop: A Bayesian Approach for Personalised Federated Learning. NeurIPS 2022 - [c104]Sergey Samsonov, Evgeny Lagutin, Marylou Gabrié, Alain Durmus, Alexey Naumov, Eric Moulines:
Local-Global MCMC kernels: the best of both worlds. NeurIPS 2022 - [c103]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Mark Rowland, Michal Valko, Pierre Ménard:
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees. NeurIPS 2022 - [i43]Alain Durmus, Éric Moulines:
On the geometric convergence for MALA under verifiable conditions. CoRR abs/2201.01951 (2022) - [i42]Daniil Tiapkin, Denis Belomestny, Eric Moulines, Alexey Naumov, Sergey Samsonov, Yunhao Tang, Michal Valko, Pierre Ménard:
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses. CoRR abs/2205.07704 (2022) - [i41]Nikita Kotelevskii, Maxime Vono, Eric Moulines, Alain Durmus:
FedPop: A Bayesian Approach for Personalised Federated Learning. CoRR abs/2206.03611 (2022) - [i40]Tom Huix, Szymon Majewski, Alain Durmus, Eric Moulines, Anna Korba:
Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study. CoRR abs/2207.03859 (2022) - [i39]Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov:
Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation. CoRR abs/2207.04475 (2022) - [i38]Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson:
BR-SNIS: Bias Reduced Self-Normalized Importance Sampling. CoRR abs/2207.06364 (2022) - [i37]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Mark Rowland, Michal Valko, Pierre Ménard:
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees. CoRR abs/2209.14414 (2022) - [i36]Vincent Plassier, Alain Durmus, Eric Moulines:
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms. CoRR abs/2211.00100 (2022) - [i35]Louis Leconte, Sholom Schechtman, Eric Moulines:
AskewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks. CoRR abs/2211.03741 (2022) - 2021
- [j69]Denis Belomestny, Leonid Iosipoi, Eric Moulines, Alexey Naumov, Sergey Samsonov:
Variance Reduction for Dependent Sequences with Applications to Stochastic Gradient MCMC. SIAM/ASA J. Uncertain. Quantification 9(2): 507-535 (2021) - [j68]Gersende Fort, P. Gach, Eric Moulines:
Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence. Stat. Comput. 31(4): 48 (2021) - [j67]Ngoc Huy Chau, Éric Moulines, Miklós Rásonyi, Sotirios Sabanis, Ying Zhang:
On Stochastic Gradient Langevin Dynamics with Dependent Data Streams: The Fully Nonconvex Case. SIAM J. Math. Data Sci. 3(3): 959-986 (2021) - [c102]Alain Durmus, Pablo Jiménez, Eric Moulines, Salem Said:
On Riemannian Stochastic Approximation Schemes with Fixed Step-Size. AISTATS 2021: 1018-1026 - [c101]Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai:
On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning. COLT 2021: 1711-1752 - [c100]Gersende Fort, Eric Moulines, Hoi-To Wai:
Geom-Spider-EM: Faster Variance Reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization. ICASSP 2021: 3135-3139 - [c99]Thomas Mesnard, Theophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas S. Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Rémi Munos:
Counterfactual Credit Assignment in Model-Free Reinforcement Learning. ICML 2021: 7654-7664 - [c98]Vincent Plassier, Maxime Vono, Alain Durmus, Eric Moulines:
DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs. ICML 2021: 8577-8587 - [c97]Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov:
Monte Carlo Variational Auto-Encoders. ICML 2021: 10247-10257 - [c96]Achille Thin, Yazid Janati El Idrissi, Sylvain Le Corff, Charles Ollion, Eric Moulines, Arnaud Doucet, Alain Durmus, Christian X. Robert:
NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform. NeurIPS 2021: 17060-17071 - [c95]Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Geneviève Robin:
Federated-EM with heterogeneity mitigation and variance reduction. NeurIPS 2021: 29553-29566 - [c94]Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai:
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize. NeurIPS 2021: 30063-30074 - [c93]Gersende Fort, Eric Moulines:
The Perturbed Prox-Preconditioned Spider Algorithm: Non-Asymptotic Convergence Bounds. SSP 2021: 96-100 - [c92]Gersende Fort, Eric Moulines:
The Perturbed Prox-Preconditioned Spider Algorithm for EM-Based Large Scale Learning. SSP 2021: 316-320 - [i34]Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai:
On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning. CoRR abs/2102.00185 (2021) - [i33]Alain Durmus, Pablo Jiménez, Éric Moulines, Salem Said:
On Riemannian Stochastic Approximation Schemes with Fixed Step-Size. CoRR abs/2102.07586 (2021) - [i32]Denis Belomestny, Ilya Levin, Eric Moulines, Alexey Naumov, Sergey Samsonov, Veronika Zorina:
Model-free policy evaluation in Reinforcement Learning via upper solutions. CoRR abs/2105.02135 (2021) - [i31]Gersende Fort, Eric Moulines:
The Perturbed Prox-Preconditioned SPIDER algorithm for EM-based large scale learning. CoRR abs/2105.11732 (2021) - [i30]Maxime Vono, Vincent Plassier, Alain Durmus, Aymeric Dieuleveut, Eric Moulines:
QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning. CoRR abs/2106.00797 (2021) - [i29]Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai:
Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize. CoRR abs/2106.01257 (2021) - [i28]Vincent Plassier, Maxime Vono, Alain Durmus, Eric Moulines:
DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm. CoRR abs/2106.06300 (2021) - [i27]Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov:
Monte Carlo Variational Auto-Encoders. CoRR abs/2106.15921 (2021) - [i26]Alain Durmus, Aurélien Enfroy, Éric Moulines, Gabriel Stoltz:
Uniform minorization condition and convergence bounds for discretizations of kinetic Langevin dynamics. CoRR abs/2107.14542 (2021) - [i25]Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Geneviève Robin:
Federated Expectation Maximization with heterogeneity mitigation and variance reduction. CoRR abs/2111.02083 (2021) - [i24]Evgeny Lagutin, Daniil Selikhanovych, Achille Thin, Sergey Samsonov, Alexey Naumov, Denis Belomestny, Maxim Panov, Eric Moulines:
Ex2MCMC: Sampling through Exploration Exploitation. CoRR abs/2111.02702 (2021) - 2020
- [j66]Belhal Karimi, Marc Lavielle, Eric Moulines:
f-SAEM: A fast stochastic approximation of the EM algorithm for nonlinear mixed effects models. Comput. Stat. Data Anal. 141: 123-138 (2020) - [j65]Denis Belomestny, Leonid Iosipoi, Eric Moulines, Alexey Naumov, Sergey Samsonov:
Variance reduction for Markov chains with application to MCMC. Stat. Comput. 30(4): 973-997 (2020) - [j64]Toni Karvonen, Silvère Bonnabel, Eric Moulines, Simo Särkkä:
On Stability of a Class of Filters for Nonlinear Stochastic Systems. SIAM J. Control. Optim. 58(4): 2023-2049 (2020) - [c91]Maxim Kaledin, Eric Moulines, Alexey Naumov, Vladislav Tadic, Hoi-To Wai:
Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise. COLT 2020: 2144-2203 - [c90]Robert Mattila, Cristian R. Rojas, Eric Moulines, Vikram Krishnamurthy, Bo Wahlberg:
Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations. ICML 2020: 6785-6796 - [c89]Gersende Fort, Eric Moulines, Hoi-To Wai:
A Stochastic Path Integral Differential EstimatoR Expectation Maximization Algorithm. NeurIPS 2020 - [i23]Nicolas Brosse, Carlos Riquelme, Alice Martin, Sylvain Gelly, Eric Moulines:
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation. CoRR abs/2001.08049 (2020) - [i22]Maxim Kaledin, Eric Moulines, Alexey Naumov, Vladislav Tadic, Hoi-To Wai:
Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise. CoRR abs/2002.01268 (2020) - [i21]Achille Thin, Nikita Kotelevskii, Jean-Stanislas Denain, Léo Grinsztajn, Alain Durmus, Maxim Panov, Eric Moulines:
MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference. CoRR abs/2002.12253 (2020) - [i20]Alain Durmus, Pablo Jiménez, Éric Moulines, Salem Said, Hoi-To Wai:
Convergence Analysis of Riemannian Stochastic Approximation Schemes. CoRR abs/2005.13284 (2020) - [i19]Gersende Fort, Eric Moulines, Hoi-To Wai:
Geom-SPIDER-EM: Faster Variance Reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization. CoRR abs/2011.12392 (2020) - [i18]Gersende Fort, Eric Moulines, Hoi-To Wai:
A Stochastic Path-Integrated Differential EstimatoR Expectation Maximization Algorithm. CoRR abs/2012.01929 (2020) - [i17]Gersende Fort, P. Gach, Eric Moulines:
Fast Incremental Expectation Maximization for finite-sum optimization: nonasymptotic convergence. CoRR abs/2012.14670 (2020)
2010 – 2019
- 2019
- [j63]Geneviève Robin, Julie Josse, Eric Moulines, Sylvain Sardy:
Low-rank model with covariates for count data with missing values. J. Multivar. Anal. 173: 416-434 (2019) - [c88]Belhal Karimi, Blazej Miasojedow, Eric Moulines, Hoi-To Wai:
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme. COLT 2019: 1944-1974 - [c87]Belhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle:
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods. NeurIPS 2019: 2833-2843 - [i16]Belhal Karimi, Blazej Miasojedow, Eric Moulines, Hoi-To Wai:
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme. CoRR abs/1902.00629 (2019) - [i15]Denis Belomestny, Leonid Iosipoi, Eric Moulines, Alexey Naumov, Sergey Samsonov:
Variance reduction for Markov chains with application to MCMC. CoRR abs/1910.03643 (2019) - [i14]Belhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle:
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods. CoRR abs/1910.12521 (2019) - [i13]Anatoli B. Juditsky, Joon Kwon, Eric Moulines:
Unifying mirror descent and dual averaging. CoRR abs/1910.13742 (2019) - 2018
- [j62]Alain Durmus, Eric Moulines, Marcelo Pereyra:
Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau. SIAM J. Imaging Sci. 11(1): 473-506 (2018) - [c86]Toni Karvonen, Silvère Bonnabel, Eric Moulines, Simo Särkkä:
Bounds on the Covariance Matrix of a Class of Kalman-Bucy Filters for Systems with Non-Linear Dynamics. CDC 2018: 7176-7181 - [c85]Sylvain Le Corff, Alain Champagne, Maurice Charbit, Gilles Nozière, Eric Moulines:
Optimizing Thermal Comfort and Energy Consumption in a Large Building without Renovation Work. DSW 2018: 41-45 - [c84]Geneviève Robin, Hoi-To Wai, Julie Josse, Olga Klopp, Eric Moulines:
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames. NeurIPS 2018: 5501-5511 - [c83]Nicolas Brosse, Alain Durmus, Eric Moulines:
The promises and pitfalls of Stochastic Gradient Langevin Dynamics. NeurIPS 2018: 8278-8288 - [c82]Gersende Fort, Laurent Risser, Yves F. Atchadé, Eric Moulines:
Stochastic Fista Algorithms: So Fast ? SSP 2018: 796-800 - [i12]Matthieu Lerasle, Zoltán Szabó, Guillaume Lecué, Gaspar Massiot, Eric Moulines:
MONK - Outlier-Robust Mean Embedding Estimation by Median-of-Means. CoRR abs/1802.04784 (2018) - [i11]Nicolas Brosse, Alain Durmus, Eric Moulines:
The promises and pitfalls of Stochastic Gradient Langevin Dynamics. CoRR abs/1811.10072 (2018) - [i10]Geneviève Robin, Hoi-To Wai, Julie Josse, Olga Klopp, Eric Moulines:
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames. CoRR abs/1812.08398 (2018) - 2017
- [j61]Florian Maire, Eric Moulines, Sidonie Lefebvre:
Online EM for functional data. Comput. Stat. Data Anal. 111: 27-47 (2017) - [j60]Ngoc Minh Nguyen, Sylvain Le Corff, Eric Moulines:
Particle rejuvenation of Rao-Blackwellized sequential Monte Carlo smoothers for conditionally linear and Gaussian models. EURASIP J. Adv. Signal Process. 2017: 54 (2017) - [j59]Alain Durmus, Sylvain Le Corff, Eric Moulines, Gareth O. Roberts:
Optimal scaling of the random walk Metropolis algorithm under L p mean differentiability. J. Appl. Probab. 54(4): 1233-1260 (2017) - [j58]Yves F. Atchadé, Gersende Fort, Eric Moulines:
On Perturbed Proximal Gradient Algorithms. J. Mach. Learn. Res. 18: 10:1-10:33 (2017) - [j57]Gersende Fort, Emmanuel Gobet, Eric Moulines:
MCMC design-based non-parametric regression for rare event. Application to nested risk computations. Monte Carlo Methods Appl. 23(1): 21-42 (2017) - [j56]Hoi-To Wai, Jean Lafond, Anna Scaglione, Eric Moulines:
Decentralized Frank-Wolfe Algorithm for Convex and Nonconvex Problems. IEEE Trans. Autom. Control. 62(11): 5522-5537 (2017) - [j55]Hajer Braham, Sana Ben Jemaa, Gersende Fort, Eric Moulines, Berna Sayraç:
Fixed Rank Kriging for Cellular Coverage Analysis. IEEE Trans. Veh. Technol. 66(5): 4212-4222 (2017) - [c81]Nicolas Brosse, Alain Durmus, Eric Moulines, Marcelo Pereyra:
Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo. COLT 2017: 319-342 - [c80]Umut Simsekli, Alain Durmus, Roland Badeau, Gaël Richard, Eric Moulines, A. Taylan Cemgil:
Parallelized Stochastic Gradient Markov Chain Monte Carlo algorithms for non-negative matrix factorization. ICASSP 2017: 2242-2246 - [c79]Hoi-To Wai, Anna Scaglione, Jean Lafond, Eric Moulines:
Fast and privacy preserving distributed low-rank regression. ICASSP 2017: 4451-4455 - 2016
- [j54]Amandine Schreck, Gersende Fort, Sylvain Le Corff, Eric Moulines:
A Shrinkage-Thresholding Metropolis Adjusted Langevin Algorithm for Bayesian Variable Selection. IEEE J. Sel. Top. Signal Process. 10(2): 366-375 (2016) - [j53]Gersende Fort, Eric Moulines, Amandine Schreck, Matti Vihola:
Convergence of Markovian Stochastic Approximation with Discontinuous Dynamics. SIAM J. Control. Optim. 54(2): 866-893 (2016) - [j52]Marjorie Jala, Céline Lévy-Leduc, Eric Moulines, Emmanuelle Conil, Joe Wiart:
Sequential Design of Computer Experiments for the Assessment of Fetus Exposure to Electromagnetic Fields. Technometrics 58(1): 30-42 (2016) - [j51]Hajer Braham, Sana Ben Jemaa, Gersende Fort, Eric Moulines, Berna Sayraç:
Spatial Prediction Under Location Uncertainty in Cellular Networks. IEEE Trans. Wirel. Commun. 15(11): 7633-7643 (2016) - [c78]Tahar Nabil, Eric Moulines, François Roueff, Jean-Marc Jicquel, Alexandre Girard:
Maximum likelihood estimation of a low-order building model. EUSIPCO 2016: 702-707 - [c77]Hoi-To Wai, Anna Scaglione, Jean Lafond, Eric Moulines:
A projection-free decentralized algorithm for non-convex optimization. GlobalSIP 2016: 475-479 - [c76]Simo Särkkä, Eric Moulines:
On the LP-convergence of a Girsanov theorem based particle filter. ICASSP 2016: 3989-3993 - [c75]Jean Lafond, Hoi-To Wai, Eric Moulines:
D-FW: Communication efficient distributed algorithms for high-dimensional sparse optimization. ICASSP 2016: 4144-4148 - [c74]Alain Durmus, Umut Simsekli, Eric Moulines, Roland Badeau, Gaël Richard:
Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo. NIPS 2016: 2047-2055 - [c73]Paul Ilhe, François Roueff, Eric Moulines, Antoine Souloumiac:
Nonparametric estimation of a shot-noise process. SSP 2016: 1-4 - [c72]François Weber, Sidonie Lefebvre, Eric Moulines, Marc Bousquet, Nicolas Roux:
Considering spatial information to improve anomaly detection in heterogeneous hyperspectral images. WHISPERS 2016: 1-7 - [i9]Hoi-To Wai, Jean Lafond, Anna Scaglione, Eric Moulines:
Decentralized Projection-free Optimization for Convex and Non-convex Problems. CoRR abs/1612.01216 (2016) - 2015
- [j50]Alain Durmus, Eric Moulines:
Quantitative bounds of convergence for geometrically ergodic Markov chain in the Wasserstein distance with application to the Metropolis Adjusted Langevin Algorithm. Stat. Comput. 25(1): 5-19 (2015) - [j49]Christelle Vergé, Cyrille Dubarry, Pierre Del Moral, Eric Moulines:
On parallel implementation of sequential Monte Carlo methods: the island particle model. Stat. Comput. 25(2): 243-260 (2015) - [c71]Eric Moulines:
The sexy job in the next ten years will be statisticians. DSAA 2015: XXIX-XXXVI - [p1]Yasir Khan, Berna Sayraç, Eric Moulines:
Centralized self-optimization of interference management in LTE-A HetNets. Design and Deployment of Small Cell Networks 2015: 363-392 - [i8]Hajer Braham, Sana Ben Jemaa, Gersende Fort, Eric Moulines, Berna Sayraç:
Fixed Rank Kriging for Cellular Coverage Analysis. CoRR abs/1505.07062 (2015) - [i7]Jean Lafond, Hoi-To Wai, Eric Moulines:
Convergence Analysis of a Stochastic Projection-free Algorithm. CoRR abs/1510.01171 (2015) - [i6]Hajer Braham, Sana Ben Jemaa, Gersende Fort, Eric Moulines, Berna Sayraç:
Spatial Prediction Under Location Uncertainty In Cellular Networks. CoRR abs/1510.03638 (2015) - 2014
- [j48]Julien Cornebise, Eric Moulines, Jimmy Olsson:
Adaptive sequential Monte Carlo by means of mixture of experts. Stat. Comput. 24(3): 317-337 (2014) - [c70]Jean Lafond, Olga Klopp, Eric Moulines, Joseph Salmon:
Probabilistic low-rank matrix completion on finite alphabets. NIPS 2014: 1727-1735 - [c69]Hajer Braham, Sana Ben Jemaa, Berna Sayraç, Gersende Fort, Eric Moulines:
Coverage mapping using spatial interpolation with field measurements. PIMRC 2014: 1743-1747 - [c68]Yasir Khan, Berna Sayraç, Eric Moulines:
Active antenna systems for centralized self-optimization of capacity in LTE-A. WCNC Workshops 2014: 166-171 - [c67]Hajer Braham, Sana Ben Jemaa, Berna Sayraç, Gersende Fort, Eric Moulines:
Low complexity spatial interpolation for cellular coverage analysis. WiOpt 2014: 188-195 - 2013
- [j47]Sidonie Lefebvre, Stéphanie Allassonnière, Jérémie Jakubowicz, Thomas Lasne, Eric Moulines:
Aircraft classification with a low resolution infrared sensor. Mach. Vis. Appl. 24(1): 175-186 (2013) - [j46]Zaïd Harchaoui, Francis R. Bach, Olivier Cappé, Eric Moulines:
Kernel-Based Methods for Hypothesis Testing: A Unified View. IEEE Signal Process. Mag. 30(4): 87-97 (2013) - [j45]Amandine Schreck, Gersende Fort, Eric Moulines:
Adaptive Equi-Energy Sampler: Convergence and Illustration. ACM Trans. Model. Comput. Simul. 23(1): 5:1-5:27 (2013) - [c66]Francis R. Bach, Eric Moulines:
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n). NIPS 2013: 773-781 - [c65]Yasir Khan, Berna Sayraç, Eric Moulines:
Centralized self-optimization of pilot powers for load balancing in LTE. PIMRC 2013: 3039-3043 - [c64]Yasir Khan, Berna Sayraç, Eric Moulines:
Surrogate Based Centralized SON: Application to Interference Mitigation in LTE-A HetNets. VTC Spring 2013: 1-5 - [c63]Yasir Khan, Berna Sayraç, Eric Moulines:
Surrogate Based Centralized Automated Optimization Applied to LTE Mobility Load Balancing. VTC Fall 2013: 1-5 - [c62]Yasir Khan, Berna Sayraç, Eric Moulines:
Centralized self-optimization in LTE-A using Active Antenna Systems. Wireless Days 2013: 1-3 - [i5]Francis R. Bach, Eric Moulines:
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n). CoRR abs/1306.2119 (2013) - 2012
- [j44]Jérémie Jakubowicz, Sidonie Lefebvre, Florian Maire, Eric Moulines:
Detecting Aircraft With a Low-Resolution Infrared Sensor. IEEE Trans. Image Process. 21(6): 3034-3041 (2012) - [c61]Marjorie Jala, Céline Lévy-Leduc, Eric Moulines, Emmanuelle Conil, Joe Wiart:
Sequential design of computer experiments for parameter estimation with application to numerical dosimetry. EUSIPCO 2012: 909-913 - [c60]Sylvain Le Corff, Gersende Fort, Eric Moulines:
New Online EM Algorithms for General Hidden Markov Models. Application to the SLAM Problem. LVA/ICA 2012: 131-138 - [c59]Florian Maire, Sidonie Lefebvre, Randal Douc, Eric Moulines:
An online learning algorithm for mixture models of deformable templates. MLSP 2012: 1-6 - [c58]Berna Sayraç, Janne Riihijärvi, Petri Mähönen, Sana Ben Jemaa, Eric Moulines, Sebastien Grimoud:
Improving coverage estimation for cellular networks with spatial bayesian prediction based on measurements. CellNet@SIGCOMM 2012: 43-48 - 2011
- [j43]Pierre Etoré, Gersende Fort, Benjamin Jourdain, Eric Moulines:
On adaptive stratification. Ann. Oper. Res. 189(1): 127-154 (2011) - [j42]Walid Hachem, Eric Moulines, François Roueff:
Error Exponents for Neyman-Pearson Detection of a Continuous-Time Gaussian Markov Process From Regular or Irregular Samples. IEEE Trans. Inf. Theory 57(6): 3899-3914 (2011) - [j41]Olaf Kouamo, Maurice Charbit, Eric Moulines, François Roueff:
Inference of a Generalized Long Memory Process in the Wavelet Domain. IEEE Trans. Signal Process. 59(12): 5759-5773 (2011) - [c57]Aurélien Garivier, Eric Moulines:
On Upper-Confidence Bound Policies for Switching Bandit Problems. ALT 2011: 174-188 - [c56]Sebastien Grimoud, Berna Sayraç, Sana Ben Jemaa, Eric Moulines:
An algorithm for fast REM construction. CrownCom 2011: 251-255 - [c55]Jianfeng Yao, Romain Couillet, Jamal Najim, Eric Moulines, Mérouane Debbah:
CLT for eigen-inference methods in cognitive radios. ICASSP 2011: 2980-2983 - [c54]Francis R. Bach, Eric Moulines:
Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning. NIPS 2011: 451-459 - [c53]Sebastien Grimoud, Berna Sayraç, Sana Ben Jemaa, Eric Moulines:
Best Sensor Selection for an Iterative REM Construction. VTC Fall 2011: 1-5 - 2010
- [j40]Steffen Barembruch, Anna Scaglione, Eric Moulines:
The expectation and sparse maximization algorithm. J. Commun. Networks 12(4): 317-329 (2010) - [c52]Steffen Barembruch, Anna Scaglione, Eric Moulines:
Maximum likelihood blind deconvolution for sparse systems. CIP 2010: 69-74 - [c51]Jérémie Jakubowicz, Sidonie Lefebvre, Eric Moulines:
Detecting aircraft with a low resolution infrared sensor. IGARSS 2010: 2475-2477 - [i4]Joffrey Villard, Pascal Bianchi, Eric Moulines, Pablo Piantanida:
High-Rate Quantization for the Neyman-Pearson Detection of Hidden Markov Processes. CoRR abs/1003.2914 (2010)
2000 – 2009
- 2009
- [j39]Steffen Barembruch, Aurélien Garivier, Eric Moulines:
On approximate maximum-likelihood methods for blind identification: how to cope with the curse of dimensionality. IEEE Trans. Signal Process. 57(11): 4247-4259 (2009) - [c50]Walid Hachem, Eric Moulines, Jamal Najim, François Roueff:
On the error exponents for detecting randomly sampled noisy diffusion processes. ICASSP 2009: 2169-2172 - [i3]Walid Hachem, Eric Moulines, François Roueff:
Error exponents for Neyman-Pearson detection of a continuous-time Gaussian Markov process from noisy irregular samples. CoRR abs/0909.4484 (2009) - 2008
- [j38]Julien Cornebise, Eric Moulines, Jimmy Olsson:
Adaptive methods for sequential importance sampling with application to state space models. Stat. Comput. 18(4): 461-480 (2008) - [c49]Julien Cornebise, Eric Moulines, Jimmy Olsson:
Adaptive methods for sequential importance sampling with application to state space models. EUSIPCO 2008: 1-5 - [c48]Sarah Filippi, Olivier Cappé, Fabrice Clérot, Eric Moulines:
A Near Optimal Policy for Channel Allocation in Cognitive Radio. EWRL 2008: 69-81 - [c47]Afef Ben Hadj Alaya-Feki, Berna Sayraç, Eric Moulines, Alain Le Cornec:
Opportunistic Spectrum Access: Online Search of Optimality. GLOBECOM 2008: 3096-3100 - [c46]Zaïd Harchaoui, Francis R. Bach, Eric Moulines:
Kernel Change-point Analysis. NIPS 2008: 609-616 - [c45]Afef Ben Hadj Alaya-Feki, Sana Ben Jemaa, Berna Sayraç, Paul Houzé, Eric Moulines:
Informed spectrum usage in cognitive radio networks: Interference cartography. PIMRC 2008: 1-5 - [c44]Afef Ben Hadj Alaya-Feki, Berna Sayraç, Alain Le Cornec, Eric Moulines:
Semi Dynamic Parameter Tuning for Optimized Opportunistic Spectrum Access. VTC Fall 2008: 1-5 - [c43]Afef Ben Hadj Alaya-Feki, Berna Sayraç, Paul Houzé, Eric Moulines:
Opportunistic Spectrum Access with IEEE 802.11 in IEEE P1900.4 Framework. WiMob 2008: 82-83 - 2007
- [j37]Afef Ben Hadj Alaya-Feki, Alain Le Cornec, Eric Moulines:
Optimization of Radio Measurements Exploitation in Wireless Mobile Networks. J. Commun. 2(7): 59-67 (2007) - [j36]Olivier Cappé, Simon J. Godsill, Eric Moulines:
An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo. Proc. IEEE 95(5): 899-924 (2007) - [j35]Thomas Trigano, Antoine Souloumiac, Thierry Montagu, François Roueff, Eric Moulines:
Statistical Pileup Correction Method for HPGe Detectors. IEEE Trans. Signal Process. 55(10): 4871-4881 (2007) - [c42]Nadir Castañeda, Maurice Charbit, Eric Moulines:
A New Approach for Mobile Localization in Multipath Scenarios. ICC 2007: 4680-4685 - [c41]Zaïd Harchaoui, Francis R. Bach, Eric Moulines:
Testing for Homogeneity with Kernel Fisher Discriminant Analysis. NIPS 2007: 609-616 - [i2]Olivier Cappé, Eric Moulines:
Online EM Algorithm for Latent Data Models. CoRR abs/0712.4273 (2007) - 2006
- [c40]Thomas Trigano, François Roueff, Eric Moulines, Antoine Souloumiac, Thierry Montagu:
Energy Spectrum Reconstruction for HPGe Detectors Using Analytical Pile-Up Correction. ICASSP (3) 2006: 592-595 - [c39]Olivier Cappé, Maurice Charbit, Eric Moulines:
Recursive Em Algorithm with Applications to Doa Estimation. ICASSP (3) 2006: 664-667 - [c38]Nadir Castañeda, Maurice Charbit, Eric Moulines:
Source Localization from Quantized Time of Arrival Measurements. ICASSP (4) 2006: 933-936 - [c37]Gersende Fort, Eric Moulines, Sean P. Meyn, Pierre Priouret:
ODE methods for Markov chain stability with applications to MCMC. VALUETOOLS 2006: 42 - 2005
- [b1]Olivier Cappé, Eric Moulines, Tobias Rydén:
Inference in hidden Markov models. Springer series in statistics, Springer 2005, ISBN 978-0-387-40264-2, pp. I-XVII, 1-651 - [j34]Marine Campedel, Eric Moulines:
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. 19(4-5): 633-659 (2005) - [j33]Christophe Andrieu, Eric Moulines, Pierre Priouret:
Stability of Stochastic Approximation under Verifiable Conditions. SIAM J. Control. Optim. 44(1): 283-312 (2005) - [c36]Christophe Andrieu, Eric Moulines, Pierre Priouret:
Stability of Stochastic Approximation under Verifiable Conditions. CDC/ECC 2005: 6656-6661 - [c35]Marine Campedel, Eric Moulines:
Méthodologie de sélection de caractéristiques pour la classification d'images satellitaires. CAP 2005: 107-108 - [c34]Olivier Cappé, Eric Moulines:
On the use of particle filtering for maximum likelihood parameter estimation. EUSIPCO 2005: 1-4 - [c33]Simon Haykin, Alfred O. Hero III, Eric Moulines:
Modeling, identification, and control of large-scale dynamical systems. ICASSP (5) 2005: 945-948 - [i1]Randal Douc, Olivier Cappé, Eric Moulines:
Comparison of Resampling Schemes for Particle Filtering. CoRR abs/cs/0507025 (2005) - 2004
- [j32]Pascal Cheung-Mon-Chan, Eric Moulines:
Global Sampling for Sequential Filtering over Discrete State Space. EURASIP J. Adv. Signal Process. 2004(15): 2242-2254 (2004) - 2003
- [j31]Samson Lasaulce, Philippe Loubaton, Eric Moulines:
A semi-blind channel estimation technique based on second-order blind method for CDMA systems. IEEE Trans. Signal Process. 51(7): 1894-1904 (2003) - 2002
- [j30]Moussa Abdi, Hassan El Nahas, Alexandre Jard, Eric Moulines:
Semidefinite positive relaxation of the maximum-likelihood criterion applied to multiuser detection in a CDMA context. IEEE Signal Process. Lett. 9(6): 165-167 (2002) - [j29]Olivier Cappé, Eric Moulines, Jean-Christophe Pesquet, Athina P. Petropulu, Xueshi Yang:
Long-range dependence and heavy-tail modeling for teletraffic data. IEEE Signal Process. Mag. 19(3): 14-27 (2002) - 2001
- [j28]Marine Campedel-Oudot, Olivier Cappé, Eric Moulines:
Estimation of the spectral envelope of voiced sounds using a penalized likelihood approach. IEEE Trans. Speech Audio Process. 9(5): 469-481 (2001) - [j27]Lisa Perros-Meilhac, Eric Moulines, Karim Abed-Meraim, Pascal Chevalier, Pierre Duhamel:
Blind identification of multipath channels: a parametric subspace approach. IEEE Trans. Signal Process. 49(7): 1468-1480 (2001) - [c32]Clifford Hurvich, Eric Moulines, Philippe Soulier:
An adaptive broadband estimator of the fractional differencing coefficient. ICASSP 2001: 3417-3420 - [c31]Samson Lasaulce, Philippe Loubaton, Eric Moulines, Soodesh Buljore:
Training-based channel estimation and de-noising for the UMTS TDD mode. VTC Fall 2001: 1908-1911 - 2000
- [j26]Rafik Aguech, Eric Moulines, Pierre Priouret:
On a Perturbation Approach for the Analysis of Stochastic Tracking Algorithms. SIAM J. Control. Optim. 39(3): 872-899 (2000) - [j25]Vincent Buchoux, Olivier Cappé, Eric Moulines, Alexei Gorokhov:
On the performance of semi-blind subspace-based channel estimation. IEEE Trans. Signal Process. 48(6): 1750-1759 (2000) - [j24]Philippe Loubaton, Eric Moulines:
On blind multiuser forward link channel estimation by the subspace method: identifiability results. IEEE Trans. Signal Process. 48(8): 2366-2376 (2000) - [j23]Jean-François Cardoso, Eric Moulines:
In-variance of subspace based estimators. IEEE Trans. Signal Process. 48(9): 2495-2505 (2000) - [c30]Samson Lasaulce, Philippe Loubaton, Eric Moulines:
Performance of a subspace based semi-blind technique in the UMTS TDD mode context. ICASSP 2000: 2481-2484
1990 – 1999
- 1999
- [j22]Lisa Perros-Meilhac, Eric Moulines, Pascal Chevalier, Pierre Duhamel:
A parametric blind subspace identification: robustness issue. IEEE Commun. Lett. 3(11): 320-322 (1999) - [j21]Olivier Cappé, Arnaud Doucet, Marc Lavielle, Eric Moulines:
Simulation-based methods for blind maximum-likelihood filter identification. Signal Process. 73(1-2): 3-25 (1999) - [c29]Philippe Loubaton, Eric Moulines:
Application of blind second order statistics MIMO identification methods to the blind CDMA forward link channel estimation. ICASSP 1999: 2543-2546 - [c28]Lisa Perros-Meilhac, Pierre Duhamel, Pascal Chevalier, Eric Moulines:
Blind knowledge based algorithms based on second order statistics. ICASSP 1999: 2901-2904 - 1998
- [j20]Vincent Buchoux, Lisa Perros-Meilhac, Olivier Cappé, Eric Moulines:
Blind and semi-blind equalization: methods and algorithms. Ann. des Télécommunications 53(11-12): 449-465 (1998) - [j19]Olivier Cappé, Chafic Mokbel, Denis Jouvet, Eric Moulines:
An algorithm for maximum likelihood estimation of hidden Markov models with unknown state-tying. IEEE Trans. Speech Audio Process. 6(1): 61-70 (1998) - [j18]Yannis Stylianou, Olivier Cappé, Eric Moulines:
Continuous probabilistic transform for voice conversion. IEEE Trans. Speech Audio Process. 6(2): 131-142 (1998) - [c27]Sandrine Vaton, Eric Moulines:
A locally stationary semi-Markovian representation for ethernet LAN traffic data. Broadband Communications 1998: 525-537 - [c26]Olivier Cappé, Randal Douc, Eric Moulines, Christian P. Robert:
Bayesian Analysis of Overdispersed Count Data with Application to Teletraffic Monitoring. COMPSTAT 1998: 215-220 - [c25]Gersende Fort, Eric Moulines, Philippe Soulier:
On the Convergence of Iterated Random Maps with Applications to the MCEM Algorithm. COMPSTAT 1998: 317-322 - [c24]Gilles Faÿ, Eric Moulines, Olivier Cappé, Frédéric Bimbot:
Polynomial quasi-harmonic models for speech analysis and synthesis. ICASSP 1998: 865-868 - [c23]Eric Moulines, Pierre Priouret, Rafik Aguech:
On a perturbation approach for the analysis of stochastic tracking algorithms. ICASSP 1998: 1681-1684 - [c22]Olivier Cappé, Vincent Buchoux, Eric Moulines:
Quasi-Newton method for maximum likelihood estimation of hidden Markov models. ICASSP 1998: 2265-2268 - 1997
- [j17]Marc Lavielle, Eric Moulines:
A simulated annealing version of the EM algorithm for non-Gaussian deconvolution. Stat. Comput. 7(4): 229-236 (1997) - [j16]Karim Abed-Meraim, Yingbo Hua, Philippe Loubaton, Éric Moulines:
Subspace method for blind identification of multichannel FIR systems in noise field with unknown spatial covariance. IEEE Signal Process. Lett. 4(5): 135-137 (1997) - [j15]Karim Abed-Meraim, Philippe Loubaton, Eric Moulines:
A subspace algorithm for certain blind identification problems. IEEE Trans. Inf. Theory 43(2): 499-511 (1997) - [j14]Karim Abed-Meraim, Jean-François Cardoso, Alexei Y. Gorokhov, Philippe Loubaton, Eric Moulines:
On subspace methods for blind identification of single-input multiple-output FIR systems. IEEE Trans. Signal Process. 45(1): 42-55 (1997) - [j13]Adel Belouchrani, Karim Abed-Meraim, Jean-François Cardoso, Eric Moulines:
A blind source separation technique using second-order statistics. IEEE Trans. Signal Process. 45(2): 434-444 (1997) - [j12]Karim Abed-Meraim, Eric Moulines, Philippe Loubaton:
Prediction error method for second-order blind identification. IEEE Trans. Signal Process. 45(3): 694-705 (1997) - [c21]Eric Moulines, Jean-François Cardoso, Elisabeth Gassiat:
Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models. ICASSP 1997: 3617-3620 - [c20]Roxana Ojeda, Jean-François Cardoso, Eric Moulines:
Asymptotically invariant Gaussianity test for causal invertible time series. ICASSP 1997: 3713-3716 - 1996
- [j11]Olivier Cappé, Eric Moulines:
Regularization techniques for discrete cepstrum estimation. IEEE Signal Process. Lett. 3(4): 100-102 (1996) - [j10]Eric Moulines, Karim Choukri:
Time-domain procedures for testing that a stationary time-series is Gaussian. IEEE Trans. Signal Process. 44(8): 2010-2025 (1996) - [c19]Alexei Gorokhov, Philippe Loubaton, Eric Moulines:
Second order blind equalization in multiple input multiple output FIR systems: a weighted least squares approach. ICASSP 1996: 2415-2418 - [c18]Eric Moulines, Jean-François Cardoso, Alexei Gorokhov, Philippe Loubaton:
Subspace methods for blind identification of SIMO-FIR systems. ICASSP 1996: 2447-2450 - 1995
- [j9]Eric Moulines, Yoshinori Sagisaka:
Editorial. Speech Commun. 16(2): 125-126 (1995) - [j8]Eric Moulines, Jean Laroche:
Non-parametric techniques for pitch-scale and time-scale modification of speech. Speech Commun. 16(2): 175-205 (1995) - [j7]Eric Moulines, Omar Ait Amrane, Yves Grenier:
The generalized multidelay adaptive filter: structure and convergence analysis. IEEE Trans. Signal Process. 43(1): 14-28 (1995) - [j6]Jean-François Cardoso, Eric Moulines:
Asymptotic performance analysis of direction-finding algorithms based on fourth-order cumulants. IEEE Trans. Signal Process. 43(1): 214-224 (1995) - [j5]Eric Moulines, Pierre Duhamel, Jean-François Cardoso, Sylvie Mayrargue:
Subspace methods for the blind identification of multichannel FIR filters. IEEE Trans. Signal Process. 43(2): 516-525 (1995) - [c17]Karim Abed-Meraim, Pierre Duhamel, David Gesbert, Philippe Loubaton, Sylvie Mayrargue, Eric Moulines, Dirk T. M. Slock:
Prediction error methods for time-domain blind identification of multichannel FIR filters. ICASSP 1995: 1968-1971 - [c16]Yannis Stylianou, Olivier Cappé, Eric Moulines:
Statistical methods for voice quality transformation. EUROSPEECH 1995: 447-450 - [c15]Yannis Stylianou, Jean Laroche, Eric Moulines:
High-quality speech modification based on a harmonic + noise model. EUROSPEECH 1995: 451-454 - 1994
- [j4]Jean-François Cardoso, Eric Moulines:
A robustness property of DOA estimators based on covariance. IEEE Trans. Signal Process. 42(11): 3285-3287 (1994) - [c14]Karim Abed-Meraim, Adel Belouchrani, Jean-François Cardoso, Eric Moulines:
Asymptotic performance of second order blind separation. ICASSP (4) 1994: 277-280 - [c13]Eric Moulines, Pierre Duhamel, Jean-François Cardoso, Sylvie Mayrargue:
Subspace methods for the blind identification of multichannel FIR filters. ICASSP (4) 1994: 573-576 - 1993
- [c12]Jean-François Cardoso, Eric Moulines:
Minimum constrast estimation with applications to array processing. ICASSP (4) 1993: 384-387 - [c11]Jean Laroche, Yannis Stylianou, Eric Moulines:
HNS: Speech modification based on a harmonic+noise model. ICASSP (2) 1993: 550-553 - 1992
- [j3]Hélène Valbret, Eric Moulines, Jean-Pierre Tubach:
Voice transformation using PSOLA technique. Speech Commun. 11(2-3): 175-187 (1992) - [c10]Omar Ait Amrane, Eric Moulines, Maurice Charbit, Yves Grenier:
Low-delay frequency domain LMS algorithm. ICASSP 1992: 9-12 - [c9]Hélène Valbret, Éric Moulines, Jean-Pierre Tubach:
Voice transformation using PSOLA technique. ICASSP 1992: 145-148 - [c8]Eric Moulines, Jean-François Cardoso:
Direction finding algorithms using fourth order statistics: asymptotic performance analysis. ICASSP 1992: 437-440 - 1991
- [c7]Hélène Valbret, Eric Moulines, Jean-Pierre Tubach:
Voice tranformation using PSOLA technique. EUROSPEECH 1991: 345-348 - 1990
- [j2]Eric Moulines, Renaud J. Di Francesco:
Detection of the glottal closure by jumps in the statistical properties of the speech signal. Speech Commun. 9(5-6): 401-418 (1990) - [j1]Eric Moulines, Francis Charpentier:
Pitch-synchronous waveform processing techniques for text-to-speech synthesis using diphones. Speech Commun. 9(5-6): 453-467 (1990) - [c6]Eric Moulines, Françoise Emerard, Danielle Larreur, J. L. Le Saint-Milon, L. Le Faucheur, F. Marty, Francis Charpentier, Christel Sorin:
A real-time French text-to-speech system generating high-quality synthetic speech. ICASSP 1990: 309-312
1980 – 1989
- 1989
- [c5]Christian Hamon, Eric Moulines, Francis Charpentier:
A diphone synthesis system based on time-domain prosodic modifications of speech. ICASSP 1989: 238-241 - [c4]Francis Charpentier, Eric Moulines:
Pitch-synchronous waveform processing techniques for text-to-speech synthesis using diphones. EUROSPEECH 1989: 2013-2019 - [c3]Renaud J. Di Francesco, Eric Moulines:
Detection of the glottal closure by jumps in the statistical properties of the signal. EUROSPEECH 1989: 2039-2042 - 1988
- [c2]Francis Charpentier, Eric Moulines:
Text-to-speech algorithms based on FFT synthesis. ICASSP 1988: 667-670 - 1987
- [c1]Christel Sorin, Raymond Descout, Christian Benoît, Françoise Emerard, C. Fluhr, Danielle Larreur, J. L. Le Saint-Milon, Eric Moulines, R. Peron:
Text-to-speech synthesis in the French electronic mail environment. ECST 1987: 2260-2263
Coauthor Index
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