Eric Moulines - RankMe

331 papers A* 50A 8B 9C 1Misc 25Journal 178Unranked 58

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Softmax and Entropy: Improving Convergence Guarantees of Policy Gradients by f-SoftArgmax Parameterization with Coupled Regularization. CoRR Safwan Labbi, Daniil Tiapkin, Paul Mangold, Eric Moulines
2026	J	`jnl`	Categorical Reparameterization with Denoising Diffusion models. CoRR Samson Gourevitch, Alain Durmus, Eric Moulines, Jimmy Olsson, Yazid Janati
2026	J	`jnl`	Development of approximate scheduling-adaptive controllers for multi-products continuous chemical processes using deep learning techniques and model predictive control. Comput. Chem. Eng. Mehdi Abou El Qassime, Ahmed Shokry, Antonio Espuña, Eric Moulines
2026	J	`jnl`	Fast and Robust Likelihood-Guided Diffusion Posterior Sampling with Amortized Variational Inference. CoRR Léon Zheng, Thomas Hirtz, Yazid Janati, Eric Moulines
2026	J	`jnl`	Guess & Guide: Gradient-Free Zero-Shot Diffusion Guidance. CoRR Abduragim Shtanchaev, Albina Ilina, Yazid Janati, Arip Asadulaev, Martin Takác, Eric Moulines
2026	J	`jnl`	High-Probability Bounds for SGD under the Polyak-Lojasiewicz Condition with Markovian Noise. CoRR Avik Kar, Siddharth Chandak, Rahul Singh, Eric Moulines, Shalabh Bhatnagar, Nicholas Bambos
2026	J	`jnl`	IDLM: Inverse-distilled Diffusion Language Models. CoRR David Li, Nikita Gushchin, Dmitry Abulkhanov, Eric Moulines, Ivan V. Oseledets, Maxim Panov, Alexander Korotin
2026	A*	`conf`	Loss-Guided Auxiliary Agents for Overcoming Mode Collapse in GFlowNets. AAAI Idriss Malek, Aya Laajil, Abhijith Sharma, Eric Moulines, Salem Lahlou
2026	J	`jnl`	Regret and Sample Complexity of Online Q-Learning via Concentration of Stochastic Approximation with Time-Inhomogeneous Markov Chains. CoRR Rahul Singh, Siddharth Chandak, Eric Moulines, Vivek S. Borkar, Nicholas Bambos
2026	J	`jnl`	When Test-Time Guidance Is Enough: Fast Image and Video Editing with Diffusion Guidance. CoRR Ahmed Ghorbel, Badr Moufad, Navid Bagheri Shouraki, Alain Oliviero Durmus, Thomas Hirtz, Eric Moulines, Jimmy Olsson, Yazid Janati
2025	A*	`conf`	A Mixture-Based Framework for Guiding Diffusion Models. ICML Yazid Janati, Badr Moufad, Mehdi Abou El Qassime, Alain Oliviero Durmus, Eric Moulines, Jimmy Olsson
2025	J	`jnl`	A Mixture-Based Framework for Guiding Diffusion Models. CoRR Yazid Janati, Badr Moufad, Mehdi Abou El Qassime, Alain Durmus, Eric Moulines, Jimmy Olsson
2025	J	`jnl`	A hybrid approach for steady-state production optimization of a real oil and gas platform: Integrating physics-based models, machine learning techniques, and field monitoring signals. Comput. Chem. Eng. Luca Trevisan, Ahmed Shokry, Marco Montini, Eric Moulines, Enrico Zio
2025	J	`jnl`	Accelerating Nash Learning from Human Feedback via Mirror Prox. CoRR Daniil Tiapkin, Daniele Calandriello, Denis Belomestny, Eric Moulines, Alexey Naumov, Kashif Rasul, Michal Valko, Pierre Ménard
2025	J	`jnl`	Adaptive Temperature Scaling with Conformal Prediction. CoRR Nikita Kotelevskii, Mohsen Guizani, Eric Moulines, Maxim Panov
2025	—	`conf`	Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect. COLING Workshops Guokan Shang, Hadi Abdine, Yousef Khoubrane, Amr Mohamed, Yassine Abbahaddou, Sofiane Ennadir, Imane Momayiz, Xuguang Ren, Eric Moulines, Preslav Nakov, Michalis Vazirgiannis, Eric P. Xing
2025	J	`jnl`	Briding Diffusion Posterior Sampling and Monte Carlo methods: a survey. CoRR Yazid Janati, Alain Durmus, Jimmy Olsson, Eric Moulines
2025	J	`jnl`	Conditional Diffusion Models with Classifier-Free Gibbs-like Guidance. CoRR Badr Moufad, Yazid Janati, Alain Durmus, Ahmed Ghorbel, Eric Moulines, Jimmy Olsson
2025	J	`jnl`	Convergence Guarantees for Federated SARSA with Local Training and Heterogeneous Agents. CoRR Paul Mangold, Eloïse Berthier, Eric Moulines
2025	J	`jnl`	Curriculum-Augmented GFlowNets For mRNA Sequence Generation. CoRR Aya Laajil, Abduragim Shtanchaev, Sajan Muhammad, Eric Moulines, Salem Lahlou
2025	J	`jnl`	Efficient Zero-Shot Inpainting with Decoupled Diffusion Guidance. CoRR Badr Moufad, Navid Bagheri Shouraki, Alain Oliviero Durmus, Thomas Hirtz, Eric Moulines, Jimmy Olsson, Yazid Janati
2025	A	`conf`	Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents. AISTATS Safwan Labbi, Daniil Tiapkin, Lorenzo Mancini, Paul Mangold, Eric Moulines
2025	A*	`conf`	Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean Field Games. ICML Antonio Ocello, Daniil Tiapkin, Lorenzo Mancini, Mathieu Laurière, Eric Moulines
2025	J	`jnl`	Finite-Sample Convergence Bounds for Trust Region Policy Optimization in Mean-Field Games. CoRR Antonio Ocello, Daniil Tiapkin, Lorenzo Mancini, Mathieu Laurière, Eric Moulines
2025	J	`jnl`	Finite-Time High-Probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation. Math. Oper. Res. Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov
2025	A*	`conf`	From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation. ICLR Nikita Kotelevskii, Vladimir Kondratyev, Martin Takác, Eric Moulines, Maxim Panov
2025	J	`jnl`	Gaussian Approximation and Multiplier Bootstrap for Stochastic Gradient Descent. CoRR Marina Sheshukova, Sergey Samsonov, Denis Belomestny, Eric Moulines, Qi-Man Shao, Zhuo-Song Zhang, Alexey Naumov
2025	J	`jnl`	Health-aware optimal charging of lithium-ion batteries using deep-neural networks-based explicit constrained model predictive control. Comput. Chem. Eng. Ahmed Shokry, Mehdi Abou El Qassime, Antonio Espuña, Eric Moulines
2025	J	`jnl`	Improved Central Limit Theorem and Bootstrap Approximations for Linear Stochastic Approximation. CoRR Bogdan Butyrin, Eric Moulines, Alexey Naumov, Sergey Samsonov, Qi-Man Shao, Zhuo-Song Zhang
2025	—	`conf`	Improving French Synthetic Speech Quality via SSML Prosody Control. ICNLSP Nassima Ould Ouali, Awais Hussain Sani, Ruben Bueno, Jonah Dauvet, Tim Luka Horstmann, Eric Moulines
2025	J	`jnl`	Improving French Synthetic Speech Quality via SSML Prosody Control. CoRR Nassima Ould Ouali, Awais Hussain Sani, Ruben Bueno, Jonah Dauvet, Tim Luka Horstmann, Eric Moulines
2025	J	`jnl`	Learning Contracts in Hierarchical Multi-Agent Systems. CoRR Antoine Scheid, Etienne Boursier, Alain Durmus, Eric Moulines, Michael I. Jordan
2025	J	`jnl`	Multidimensional Uncertainty Quantification via Optimal Transport. CoRR Nikita Kotelevskii, Maiya Goloburda, Vladimir Kondratyev, Alexander Fishkov, Mohsen Guizani, Eric Moulines, Maxim Panov
2025	J	`jnl`	Neural Optimal Transport Meets Multivariate Conformal Prediction. CoRR Vladimir Kondratyev, Alexander Fishkov, Nikita Kotelevskii, Mahmoud Hegazy, Rémi Flamary, Maxim Panov, Eric Moulines
2025	A*	`conf`	Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation. ICLR Marina Sheshukova, Denis Belomestny, Alain Oliviero Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov
2025	J	`jnl`	On Global Convergence Rates for Federated Policy Gradient under Heterogeneous Environment. CoRR Safwan Labbi, Paul Mangold, Daniil Tiapkin, Eric Moulines
2025	J	`jnl`	Online Decision-Focused Learning. CoRR Aymeric Capitaine, Maxime Haddouche, Eric Moulines, Michael I. Jordan, Etienne Boursier, Alain Durmus
2025	A*	`conf`	Prediction-Aware Learning in Multi-Agent Systems. ICML Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael I. Jordan, Alain Oliviero Durmus
2025	J	`jnl`	Prediction-Aware Learning in Multi-Agent Systems. CoRR Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael I. Jordan, Alain Durmus
2025	A*	`conf`	Probabilistic Conformal Prediction with Approximate Conditional Validity. ICLR Vincent Plassier, Alexander Fishkov, Mohsen Guizani, Maxim Panov, Eric Moulines
2025	A*	`conf`	Rectifying Conformity Scores for Better Conditional Coverage. ICML Vincent Plassier, Alexander Fishkov, Victor Dheur, Mohsen Guizani, Souhaib Ben Taieb, Maxim Panov, Eric Moulines
2025	J	`jnl`	Rectifying Conformity Scores for Better Conditional Coverage. CoRR Vincent Plassier, Alexander Fishkov, Victor Dheur, Mohsen Guizani, Souhaib Ben Taieb, Maxim Panov, Eric Moulines
2025	A	`conf`	Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation. AISTATS Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines
2025	A*	`conf`	Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up. ICML Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Eric Moulines
2025	J	`jnl`	Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up. CoRR Paul Mangold, Alain Durmus, Aymeric Dieuleveut, Eric Moulines
2025	J	`jnl`	Statistical inference for Linear Stochastic Approximation with Markovian Noise. CoRR Sergey Samsonov, Marina Sheshukova, Eric Moulines, Alexey Naumov
2025	A*	`conf`	Variational Diffusion Posterior Sampling with Midpoint Guidance. ICLR Badr Moufad, Yazid Janati, Lisa Bedin, Alain Oliviero Durmus, Randal Douc, Eric Moulines, Jimmy Olsson
2025	J	`jnl`	Y-shaped Generative Flows. CoRR Arip Asadulaev, Semyon Semenov, Abduragim Shtanchaev, Eric Moulines, Fakhri Karray, Martin Takác
2025	J	`jnl`	torchsom: The Reference PyTorch Library for Self-Organizing Maps. CoRR Louis Berthier, Ahmed Shokry, Maxime Moreaud, Guillaume Ramelet, Eric Moulines
2024	J	`jnl`	Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect. CoRR Guokan Shang, Hadi Abdine, Yousef Khoubrane, Amr Mohamed, Yassine Abbahaddou, Sofiane Ennadir, Imane Momayiz, Xuguang Ren, Eric Moulines, Preslav Nakov, Michalis Vazirgiannis, Eric P. Xing
2024	J	`jnl`	Bayesian ECG reconstruction using denoising diffusion generative models. CoRR Gabriel Victorino Cardoso, Lisa Bedin, Josselin Duchateau, Rémi Dubois, Eric Moulines
2024	J	`jnl`	Conditionally valid Probabilistic Conformal Prediction. CoRR Vincent Plassier, Alexander Fishkov, Maxim Panov, Eric Moulines
2024	—	`conf`	Deep Reinforcement Learning Algorithms for Hybrid V2X Communication: A Benchmarking Study. ICC Workshops Fouzi Boukhalfa, Réda Alami, Mastane Achab, Eric Moulines, Mehdi Bennis, Thierry Lestable
2024	A*	`conf`	Demonstration-Regularized RL. ICLR Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
2024	J	`jnl`	Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors. CoRR Yazid Janati El Idrissi, Alain Durmus, Eric Moulines, Jimmy Olsson
2024	A*	`conf`	Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors. NeurIPS Yazid Janati, Badr Moufad, Alain Durmus, Eric Moulines, Jimmy Olsson
2024	A	`conf`	Efficient Conformal Prediction under Data Heterogeneity. AISTATS Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov
2024	Misc	`conf`	FAVANO: Federated Averaging with Asynchronous Nodes. ICASSP Louis Leconte, Van Minh Nguyen, Eric Moulines
2024	J	`jnl`	Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents. CoRR Safwan Labbi, Daniil Tiapkin, Lorenzo Mancini, Paul Mangold, Eric Moulines
2024	A*	`conf`	Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning. NeurIPS Sergey Samsonov, Eric Moulines, Qi-Man Shao, Zhuo-Song Zhang, Alexey Naumov
2024	J	`jnl`	Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning. CoRR Sergey Samsonov, Eric Moulines, Qi-Man Shao, Zhuo-Song Zhang, Alexey Naumov
2024	A*	`conf`	Improved High-Probability Bounds for the Temporal Difference Learning Algorithm via Exponential Stability. COLT Sergey Samsonov, Daniil Tiapkin, Alexey Naumov, Eric Moulines
2024	A*	`conf`	Incentivized Learning in Principal-Agent Bandit Games. ICML Antoine Scheid, Daniil Tiapkin, Etienne Boursier, Aymeric Capitaine, Eric Moulines, Michael I. Jordan, El-Mahdi El-Mhamdi, Alain Oliviero Durmus
2024	J	`jnl`	Incentivized Learning in Principal-Agent Bandit Games. CoRR Antoine Scheid, Daniil Tiapkin, Etienne Boursier, Aymeric Capitaine, El Mahdi El Mhamdi, Eric Moulines, Michael I. Jordan, Alain Durmus
2024	J	`jnl`	Joint Channel Selection using FedDRL in V2X. CoRR Lorenzo Mancini, Safwan Labbi, Karim Abed-Meraim, Fouzi Boukhalfa, Alain Durmus, Paul Mangold, Eric Moulines
2024	A*	`conf`	Learning to Mitigate Externalities: the Coase Theorem with Hindsight Rationality. NeurIPS Antoine Scheid, Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael I. Jordan, Alain Durmus
2024	A*	`conf`	Leveraging an ECG Beat Diffusion Model for Morphological Reconstruction from Indirect Signals. NeurIPS Lisa Bedin, Gabriel Cardoso, Josselin Duchateau, Rémi Dubois, Eric Moulines
2024	J	`jnl`	Mitigating Externalities while Learning: an Online Version of the Coase Theorem. CoRR Antoine Scheid, Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael I. Jordan, Alain Durmus
2024	A*	`conf`	Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems. ICLR Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff, Eric Moulines
2024	J	`jnl`	Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson-Romberg Extrapolation. CoRR Marina Sheshukova, Denis Belomestny, Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov
2024	J	`jnl`	Optimal Design for Reward Modeling in RLHF. CoRR Antoine Scheid, Etienne Boursier, Alain Durmus, Michael I. Jordan, Pierre Ménard, Eric Moulines, Michal Valko
2024	A*	`conf`	Piecewise deterministic generative models. NeurIPS Andrea Bertazzi, Dario Shariatian, Umut Simsekli, Eric Moulines, Alain Durmus
2024	J	`jnl`	Piecewise deterministic generative models. CoRR Andrea Bertazzi, Alain Oliviero Durmus, Dario Shariatian, Umut Simsekli, Eric Moulines
2024	A	`conf`	Queuing dynamics of asynchronous Federated Learning. AISTATS Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines
2024	J	`jnl`	Queuing dynamics of asynchronous Federated Learning. CoRR Louis Leconte, Matthieu Jonckheere, Sergey Samsonov, Eric Moulines
2024	J	`jnl`	Rates of convergence for density estimation with generative adversarial networks. J. Mach. Learn. Res. Nikita Puchkin, Sergey Samsonov, Denis Belomestny, Eric Moulines, Alexey Naumov
2024	J	`jnl`	ReALLM: A general framework for LLM compression and fine-tuning. CoRR Louis Leconte, Lisa Bedin, Van Minh Nguyen, Eric Moulines
2024	J	`jnl`	Refined Analysis of Federated Averaging's Bias and Federated Richardson-Romberg Extrapolation. CoRR Paul Mangold, Alain Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines
2024	J	`jnl`	SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning. CoRR Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Réda Alami, Alexey Naumov, Eric Moulines
2024	A*	`conf`	SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning. NeurIPS Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Réda Alami, Alexey Naumov, Eric Moulines
2024	A*	`conf`	Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians. ICML Tom Huix, Anna Korba, Alain Oliviero Durmus, Eric Moulines
2024	J	`jnl`	Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians. CoRR Tom Huix, Anna Korba, Alain Durmus, Eric Moulines
2024	A*	`conf`	Unravelling in Collaborative Learning. NeurIPS Aymeric Capitaine, Etienne Boursier, Antoine Scheid, Eric Moulines, Michael I. Jordan, El-Mahdi El-Mhamdi, Alain Durmus
2024	J	`jnl`	Unravelling in Collaborative Learning. CoRR Aymeric Capitaine, Etienne Boursier, Antoine Scheid, Eric Moulines, Michael I. Jordan, El-Mahdi El-Mhamdi, Alain Durmus
2024	J	`jnl`	Variational Diffusion Posterior Sampling with Midpoint Guidance. CoRR Badr Moufad, Yazid Janati, Lisa Bedin, Alain Durmus, Randal Douc, Eric Moulines, Jimmy Olsson
2023	A	`conf`	ASkewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks. AISTATS Louis Leconte, Sholom Schechtman, Eric Moulines
2023	A*	`conf`	Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. ICML Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov
2023	J	`jnl`	Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. CoRR Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov
2023	J	`jnl`	Deep Reinforcement Learning Algorithms for Hybrid V2X Communication: A Benchmarking Study. CoRR Fouzi Boukhalfa, Réda Alami, Mastane Achab, Eric Moulines, Mehdi Bennis
2023	J	`jnl`	Demonstration-Regularized RL. CoRR Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
2023	J	`jnl`	Efficient Conformal Prediction under Data Heterogeneity. CoRR Vincent Plassier, Nikita Kotelevskii, Aleksandr Rubashevskii, Fedor Noskov, Maksim Velikanov, Alexander Fishkov, Samuel Horváth, Martin Takác, Eric Moulines, Maxim Panov
2023	J	`jnl`	FAVAS: Federated AVeraging with ASynchronous clients. CoRR Louis Leconte, Van Minh Nguyen, Eric Moulines
2023	A*	`conf`	Fast Rates for Maximum Entropy Exploration. ICML Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Ménard
2023	J	`jnl`	Fast Rates for Maximum Entropy Exploration. CoRR Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Ménard
2023	A	`conf`	Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms. AISTATS Vincent Plassier, Eric Moulines, Alain Durmus
2023	—	`conf`	Federated Boolean Neural Networks Learning. FMEC Louis Leconte, Van Minh Nguyen, Eric Moulines
2023	J	`jnl`	Finite-Sample Analysis of the Temporal Difference Learning. CoRR Sergey Samsonov, Daniil Tiapkin, Alexey Naumov, Eric Moulines
2023	A*	`conf`	First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities. NeurIPS Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander V. Gasnikov, Alexey Naumov, Eric Moulines
2023	J	`jnl`	First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities. CoRR Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander V. Gasnikov, Alexey Naumov, Eric Moulines
2023	A*	`conf`	Model-free Posterior Sampling via Learning Rate Randomization. NeurIPS Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
2023	J	`jnl`	Model-free Posterior Sampling via Learning Rate Randomization. CoRR Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
2023	J	`jnl`	Monte Carlo guided Diffusion for Bayesian linear inverse problems. CoRR Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff, Eric Moulines
2023	A*	`conf`	On Sampling with Approximate Transport Maps. ICML Louis Grenioux, Alain Oliviero Durmus, Eric Moulines, Marylou Gabrié
2023	J	`jnl`	One-Step Distributional Reinforcement Learning. CoRR Mastane Achab, Réda Alami, Yasser Abdelaziz Dahou Djilali, Kirill Fedyanin, Eric Moulines
2023	J	`jnl`	One-Step Distributional Reinforcement Learning. Trans. Mach. Learn. Res. Mastane Achab, Réda Alami, Yasser Abdelaziz Dahou Djilali, Kirill Fedyanin, Eric Moulines
2023	A*	`conf`	Quantile Credit Assignment. ICML 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
2023	—	`conf`	Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes. CoLLAs Réda Alami, Mohammed Mahfoud, Eric Moulines
2023	J	`jnl`	Restarted Bayesian Online Change-point Detection for Non-Stationary Markov Decision Processes. CoRR Réda Alami, Mohammed Mahfoud, Eric Moulines
2023	A*	`conf`	State and parameter learning with PARIS particle Gibbs. ICML Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff, Eric Moulines, Jimmy Olsson
2023	J	`jnl`	Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning. IEEE Trans. Signal Process. Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Hoi-To Wai
2023	J	`jnl`	Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization. CoRR Gersende Fort, Eric Moulines
2023	J	`jnl`	Stochastic variable metric proximal gradient with variance reduction for non-convex composite optimization. Stat. Comput. Gersende Fort, Eric Moulines
2022	—	`conf`	A Patient-Specific Single Equivalent Dipole Model. CinC Gabriel Cardoso, Geneviève Robin, Andony Arrieula, Mark Potse, Michel Haïssaguerre, Eric Moulines, Rémi Dubois
2022	J	`jnl`	AskewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks. CoRR Louis Leconte, Sholom Schechtman, Eric Moulines
2022	A*	`conf`	BR-SNIS: Bias Reduced Self-Normalized Importance Sampling. NeurIPS Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson
2022	J	`jnl`	BR-SNIS: Bias Reduced Self-Normalized Importance Sampling. CoRR Gabriel Cardoso, Sergey Samsonov, Achille Thin, Eric Moulines, Jimmy Olsson
2022	A*	`conf`	Diffusion bridges vector quantized variational autoencoders. ICML Max Cohen, Guillaume Quispe, Sylvain Le Corff, Charles Ollion, Eric Moulines
2022	A*	`conf`	FedPop: A Bayesian Approach for Personalised Federated Learning. NeurIPS Nikita Kotelevskii, Maxime Vono, Alain Durmus, Eric Moulines
2022	J	`jnl`	FedPop: A Bayesian Approach for Personalised Federated Learning. CoRR Nikita Kotelevskii, Maxime Vono, Eric Moulines, Alain Durmus
2022	J	`jnl`	Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms. CoRR Vincent Plassier, Alain Durmus, Eric Moulines
2022	J	`jnl`	Finite-time High-probability Bounds for Polyak-Ruppert Averaged Iterates of Linear Stochastic Approximation. CoRR Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov
2022	A*	`conf`	From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses. ICML Daniil Tiapkin, Denis Belomestny, Eric Moulines, Alexey Naumov, Sergey Samsonov, Yunhao Tang, Michal Valko, Pierre Ménard
2022	J	`jnl`	From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses. CoRR Daniil Tiapkin, Denis Belomestny, Eric Moulines, Alexey Naumov, Sergey Samsonov, Yunhao Tang, Michal Valko, Pierre Ménard
2022	A*	`conf`	Local-Global MCMC kernels: the best of both worlds. NeurIPS Sergey Samsonov, Evgeny Lagutin, Marylou Gabrié, Alain Durmus, Alexey Naumov, Eric Moulines
2022	B	`conf`	Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex Problems. ALT Belhal Karimi, Hoi-To Wai, Eric Moulines, Ping Li
2022	A*	`conf`	Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees. NeurIPS Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Mark Rowland, Michal Valko, Pierre Ménard
2022	J	`jnl`	Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees. CoRR Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Mark Rowland, Michal Valko, Pierre Ménard
2022	A	`conf`	QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning. AISTATS Maxime Vono, Vincent Plassier, Alain Durmus, Aymeric Dieuleveut, Eric Moulines
2022	J	`jnl`	Variance reduction for additive functionals of Markov chains via martingale representations. Stat. Comput. Denis Belomestny, Eric Moulines, Sergey Samsonov
2022	J	`jnl`	Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study. CoRR Tom Huix, Szymon Majewski, Alain Durmus, Eric Moulines, Anna Korba
2021	A*	`conf`	Counterfactual Credit Assignment in Model-Free Reinforcement Learning. ICML 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
2021	A*	`conf`	DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm via Langevin Monte Carlo within Gibbs. ICML Vincent Plassier, Maxime Vono, Alain Durmus, Eric Moulines
2021	J	`jnl`	DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm. CoRR Vincent Plassier, Maxime Vono, Alain Durmus, Eric Moulines
2021	J	`jnl`	Ex CoRR Evgeny Lagutin, Daniil Selikhanovych, Achille Thin, Sergey Samsonov, Alexey Naumov, Denis Belomestny, Maxim Panov, Eric Moulines
2021	J	`jnl`	Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence. Stat. Comput. Gersende Fort, P. Gach, Eric Moulines
2021	J	`jnl`	Federated Expectation Maximization with heterogeneity mitigation and variance reduction. CoRR Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Geneviève Robin
2021	A*	`conf`	Federated-EM with heterogeneity mitigation and variance reduction. NeurIPS Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Geneviève Robin
2021	Misc	`conf`	Geom-Spider-EM: Faster Variance Reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization. ICASSP Gersende Fort, Eric Moulines, Hoi-To Wai
2021	J	`jnl`	Model-free policy evaluation in Reinforcement Learning via upper solutions. CoRR Denis Belomestny, Ilya Levin, Eric Moulines, Alexey Naumov, Sergey Samsonov, Veronika Zorina
2021	A*	`conf`	Monte Carlo Variational Auto-Encoders. ICML Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov
2021	J	`jnl`	Monte Carlo Variational Auto-Encoders. CoRR Achille Thin, Nikita Kotelevskii, Arnaud Doucet, Alain Durmus, Eric Moulines, Maxim Panov
2021	A*	`conf`	NEO: Non Equilibrium Sampling on the Orbits of a Deterministic Transform. NeurIPS Achille Thin, Yazid Janati El Idrissi, Sylvain Le Corff, Charles Ollion, Eric Moulines, Arnaud Doucet, Alain Durmus, Christian X. Robert
2021	A	`conf`	On Riemannian Stochastic Approximation Schemes with Fixed Step-Size. AISTATS Alain Durmus, Pablo Jiménez, Eric Moulines, Salem Said
2021	A*	`conf`	On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning. COLT Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai
2021	J	`jnl`	On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning. CoRR Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Hoi-To Wai
2021	J	`jnl`	QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning. CoRR Maxime Vono, Vincent Plassier, Alain Durmus, Aymeric Dieuleveut, Eric Moulines
2021	J	`jnl`	The Perturbed Prox-Preconditioned SPIDER algorithm for EM-based large scale learning. CoRR Gersende Fort, Eric Moulines
2021	—	`conf`	The Perturbed Prox-Preconditioned Spider Algorithm for EM-Based Large Scale Learning. SSP Gersende Fort, Eric Moulines
2021	—	`conf`	The Perturbed Prox-Preconditioned Spider Algorithm: Non-Asymptotic Convergence Bounds. SSP Gersende Fort, Eric Moulines
2021	A*	`conf`	Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize. NeurIPS Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai
2021	J	`jnl`	Tight High Probability Bounds for Linear Stochastic Approximation with Fixed Stepsize. CoRR Alain Durmus, Eric Moulines, Alexey Naumov, Sergey Samsonov, Kevin Scaman, Hoi-To Wai
2021	J	`jnl`	Variance Reduction for Dependent Sequences with Applications to Stochastic Gradient MCMC. SIAM/ASA J. Uncertain. Quantification Denis Belomestny, Leonid Iosipoi, Eric Moulines, Alexey Naumov, Sergey Samsonov
2020	A*	`conf`	A Stochastic Path Integral Differential EstimatoR Expectation Maximization Algorithm. NeurIPS Gersende Fort, Eric Moulines, Hoi-To Wai
2020	J	`jnl`	A Stochastic Path-Integrated Differential EstimatoR Expectation Maximization Algorithm. CoRR Gersende Fort, Eric Moulines, Hoi-To Wai
2020	J	`jnl`	Fast Incremental Expectation Maximization for finite-sum optimization: nonasymptotic convergence. CoRR Gersende Fort, P. Gach, Eric Moulines
2020	A*	`conf`	Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations. ICML Robert Mattila, Cristian R. Rojas, Eric Moulines, Vikram Krishnamurthy, Bo Wahlberg
2020	A*	`conf`	Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise. COLT Maxim Kaledin, Eric Moulines, Alexey Naumov, Vladislav Tadic, Hoi-To Wai
2020	J	`jnl`	Finite Time Analysis of Linear Two-timescale Stochastic Approximation with Markovian Noise. CoRR Maxim Kaledin, Eric Moulines, Alexey Naumov, Vladislav Tadic, Hoi-To Wai
2020	J	`jnl`	Geom-SPIDER-EM: Faster Variance Reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization. CoRR Gersende Fort, Eric Moulines, Hoi-To Wai
2020	J	`jnl`	MetFlow: A New Efficient Method for Bridging the Gap between Markov Chain Monte Carlo and Variational Inference. CoRR Achille Thin, Nikita Kotelevskii, Jean-Stanislas Denain, Léo Grinsztajn, Alain Durmus, Maxim Panov, Eric Moulines
2020	J	`jnl`	On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation. CoRR Nicolas Brosse, Carlos Riquelme, Alice Martin, Sylvain Gelly, Eric Moulines
2020	J	`jnl`	On Stability of a Class of Filters for Nonlinear Stochastic Systems. SIAM J. Control. Optim. Toni Karvonen, Silvère Bonnabel, Eric Moulines, Simo Särkkä
2020	J	`jnl`	Variance reduction for Markov chains with application to MCMC. Stat. Comput. Denis Belomestny, Leonid Iosipoi, Eric Moulines, Alexey Naumov, Sergey Samsonov
2020	J	`jnl`	f-SAEM: A fast stochastic approximation of the EM algorithm for nonlinear mixed effects models. Comput. Stat. Data Anal. Belhal Karimi, Marc Lavielle, Eric Moulines
2019	J	`jnl`	Low-rank model with covariates for count data with missing values. J. Multivar. Anal. Geneviève Robin, Julie Josse, Eric Moulines, Sylvain Sardy
2019	A*	`conf`	Non-asymptotic Analysis of Biased Stochastic Approximation Scheme. COLT Belhal Karimi, Blazej Miasojedow, Eric Moulines, Hoi-To Wai
2019	J	`jnl`	Non-asymptotic Analysis of Biased Stochastic Approximation Scheme. CoRR Belhal Karimi, Blazej Miasojedow, Eric Moulines, Hoi-To Wai
2019	A*	`conf`	On the Global Convergence of (Fast) Incremental Expectation Maximization Methods. NeurIPS Belhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle
2019	J	`jnl`	On the Global Convergence of (Fast) Incremental Expectation Maximization Methods. CoRR Belhal Karimi, Hoi-To Wai, Eric Moulines, Marc Lavielle
2019	J	`jnl`	Unifying mirror descent and dual averaging. CoRR Anatoli B. Juditsky, Joon Kwon, Eric Moulines
2019	J	`jnl`	Variance reduction for Markov chains with application to MCMC. CoRR Denis Belomestny, Leonid Iosipoi, Eric Moulines, Alexey Naumov, Sergey Samsonov
2018	—	`conf`	Bounds on the Covariance Matrix of a Class of Kalman-Bucy Filters for Systems with Non-Linear Dynamics. CDC Toni Karvonen, Silvère Bonnabel, Eric Moulines, Simo Särkkä
2018	J	`jnl`	Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau. SIAM J. Imaging Sci. Alain Durmus, Eric Moulines, Marcelo Pereyra
2018	A*	`conf`	Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames. NeurIPS Geneviève Robin, Hoi-To Wai, Julie Josse, Olga Klopp, Eric Moulines
2018	J	`jnl`	Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames. CoRR Geneviève Robin, Hoi-To Wai, Julie Josse, Olga Klopp, Eric Moulines
2018	J	`jnl`	MONK - Outlier-Robust Mean Embedding Estimation by Median-of-Means. CoRR Matthieu Lerasle, Zoltán Szabó, Guillaume Lecué, Gaspar Massiot, Eric Moulines
2018	—	`conf`	Optimizing Thermal Comfort and Energy Consumption in a Large Building without Renovation Work. DSW Sylvain Le Corff, Alain Champagne, Maurice Charbit, Gilles Nozière, Eric Moulines
2018	—	`conf`	Stochastic Fista Algorithms: So Fast ? SSP Gersende Fort, Laurent Risser, Yves F. Atchadé, Eric Moulines
2018	A*	`conf`	The promises and pitfalls of Stochastic Gradient Langevin Dynamics. NeurIPS Nicolas Brosse, Alain Durmus, Eric Moulines
2018	J	`jnl`	The promises and pitfalls of Stochastic Gradient Langevin Dynamics. CoRR Nicolas Brosse, Alain Durmus, Eric Moulines
2017	J	`jnl`	Decentralized Frank-Wolfe Algorithm for Convex and Nonconvex Problems. IEEE Trans. Autom. Control. Hoi-To Wai, Jean Lafond, Anna Scaglione, Eric Moulines
2017	Misc	`conf`	Fast and privacy preserving distributed low-rank regression. ICASSP Hoi-To Wai, Anna Scaglione, Jean Lafond, Eric Moulines
2017	J	`jnl`	Fixed Rank Kriging for Cellular Coverage Analysis. IEEE Trans. Veh. Technol. Hajer Braham, Sana Ben Jemaa, Gersende Fort, Eric Moulines, Berna Sayraç
2017	J	`jnl`	MCMC design-based non-parametric regression for rare event. Application to nested risk computations. Monte Carlo Methods Appl. Gersende Fort, Emmanuel Gobet, Eric Moulines
2017	J	`jnl`	On Perturbed Proximal Gradient Algorithms. J. Mach. Learn. Res. Yves F. Atchadé, Gersende Fort, Eric Moulines
2017	J	`jnl`	Online EM for functional data. Comput. Stat. Data Anal. Florian Maire, Eric Moulines, Sidonie Lefebvre
2017	J	`jnl`	Optimal scaling of the random walk Metropolis algorithm under L p mean differentiability. J. Appl. Probab. Alain Durmus, Sylvain Le Corff, Eric Moulines, Gareth O. Roberts
2017	Misc	`conf`	Parallelized Stochastic Gradient Markov Chain Monte Carlo algorithms for non-negative matrix factorization. ICASSP Umut Simsekli, Alain Durmus, Roland Badeau, Gaël Richard, Eric Moulines, A. Taylan Cemgil
2017	J	`jnl`	Particle rejuvenation of Rao-Blackwellized sequential Monte Carlo smoothers for conditionally linear and Gaussian models. EURASIP J. Adv. Signal Process. Ngoc Minh Nguyen, Sylvain Le Corff, Eric Moulines
2017	A*	`conf`	Sampling from a log-concave distribution with compact support with proximal Langevin Monte Carlo. COLT Nicolas Brosse, Alain Durmus, Eric Moulines, Marcelo Pereyra
2016	J	`jnl`	A Shrinkage-Thresholding Metropolis Adjusted Langevin Algorithm for Bayesian Variable Selection. IEEE J. Sel. Top. Signal Process. Amandine Schreck, Gersende Fort, Sylvain Le Corff, Eric Moulines
2016	—	`conf`	A projection-free decentralized algorithm for non-convex optimization. GlobalSIP Hoi-To Wai, Anna Scaglione, Jean Lafond, Eric Moulines
2016	—	`conf`	Considering spatial information to improve anomaly detection in heterogeneous hyperspectral images. WHISPERS François Weber, Sidonie Lefebvre, Eric Moulines, Marc Bousquet, Nicolas Roux
2016	J	`jnl`	Convergence of Markovian Stochastic Approximation with Discontinuous Dynamics. SIAM J. Control. Optim. Gersende Fort, Eric Moulines, Amandine Schreck, Matti Vihola
2016	Misc	`conf`	D-FW: Communication efficient distributed algorithms for high-dimensional sparse optimization. ICASSP Jean Lafond, Hoi-To Wai, Eric Moulines
2016	J	`jnl`	Decentralized Projection-free Optimization for Convex and Non-convex Problems. CoRR Hoi-To Wai, Jean Lafond, Anna Scaglione, Eric Moulines
2016	—	`conf`	Maximum likelihood estimation of a low-order building model. EUSIPCO Tahar Nabil, Eric Moulines, François Roueff, Jean-Marc Jicquel, Alexandre Girard
2016	—	`conf`	Nonparametric estimation of a shot-noise process. SSP Paul Ilhe, François Roueff, Eric Moulines, Antoine Souloumiac
2016	Misc	`conf`	On the LP-convergence of a Girsanov theorem based particle filter. ICASSP Simo Särkkä, Eric Moulines
2016	J	`jnl`	Sequential Design of Computer Experiments for the Assessment of Fetus Exposure to Electromagnetic Fields. Technometrics Marjorie Jala, Céline Lévy-Leduc, Eric Moulines, Emmanuelle Conil, Joe Wiart
2016	J	`jnl`	Spatial Prediction Under Location Uncertainty in Cellular Networks. IEEE Trans. Wirel. Commun. Hajer Braham, Sana Ben Jemaa, Gersende Fort, Eric Moulines, Berna Sayraç
2016	—	`conf`	Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo. NIPS Alain Durmus, Umut Simsekli, Eric Moulines, Roland Badeau, Gaël Richard
2015	—	`ch.`	Centralized self-optimization of interference management in LTE-A HetNets. Design and Deployment of Small Cell Networks Yasir Khan, Berna Sayraç, Eric Moulines
2015	J	`jnl`	Convergence Analysis of a Stochastic Projection-free Algorithm. CoRR Jean Lafond, Hoi-To Wai, Eric Moulines
2015	J	`jnl`	Fixed Rank Kriging for Cellular Coverage Analysis. CoRR Hajer Braham, Sana Ben Jemaa, Gersende Fort, Eric Moulines, Berna Sayraç
2015	J	`jnl`	On parallel implementation of sequential Monte Carlo methods: the island particle model. Stat. Comput. Christelle Vergé, Cyrille Dubarry, Pierre Del Moral, Eric Moulines
2015	J	`jnl`	Quantitative bounds of convergence for geometrically ergodic Markov chain in the Wasserstein distance with application to the Metropolis Adjusted Langevin Algorithm. Stat. Comput. Alain Durmus, Eric Moulines
2015	J	`jnl`	Spatial Prediction Under Location Uncertainty In Cellular Networks. CoRR Hajer Braham, Sana Ben Jemaa, Gersende Fort, Eric Moulines, Berna Sayraç
2015	B	`conf`	The sexy job in the next ten years will be statisticians. DSAA Eric Moulines
2014	—	`conf`	Active antenna systems for centralized self-optimization of capacity in LTE-A. WCNC Workshops Yasir Khan, Berna Sayraç, Eric Moulines
2014	J	`jnl`	Adaptive sequential Monte Carlo by means of mixture of experts. Stat. Comput. Julien Cornebise, Eric Moulines, Jimmy Olsson
2014	B	`conf`	Coverage mapping using spatial interpolation with field measurements. PIMRC Hajer Braham, Sana Ben Jemaa, Berna Sayraç, Gersende Fort, Eric Moulines
2014	B	`conf`	Low complexity spatial interpolation for cellular coverage analysis. WiOpt Hajer Braham, Sana Ben Jemaa, Berna Sayraç, Gersende Fort, Eric Moulines
2014	—	`conf`	Probabilistic low-rank matrix completion on finite alphabets. NIPS Jean Lafond, Olga Klopp, Eric Moulines, Joseph Salmon
2013	J	`jnl`	Adaptive Equi-Energy Sampler: Convergence and Illustration. ACM Trans. Model. Comput. Simul. Amandine Schreck, Gersende Fort, Eric Moulines
2013	J	`jnl`	Aircraft classification with a low resolution infrared sensor. Mach. Vis. Appl. Sidonie Lefebvre, Stéphanie Allassonnière, Jérémie Jakubowicz, Thomas Lasne, Eric Moulines
2013	—	`conf`	Centralized self-optimization in LTE-A using Active Antenna Systems. Wireless Days Yasir Khan, Berna Sayraç, Eric Moulines
2013	B	`conf`	Centralized self-optimization of pilot powers for load balancing in LTE. PIMRC Yasir Khan, Berna Sayraç, Eric Moulines
2013	J	`jnl`	Kernel-Based Methods for Hypothesis Testing: A Unified View. IEEE Signal Process. Mag. Zaïd Harchaoui, Francis R. Bach, Olivier Cappé, Eric Moulines
2013	—	`conf`	Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n). NIPS Francis R. Bach, Eric Moulines
2013	J	`jnl`	Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n). CoRR Francis R. Bach, Eric Moulines
2013	—	`conf`	Surrogate Based Centralized Automated Optimization Applied to LTE Mobility Load Balancing. VTC Fall Yasir Khan, Berna Sayraç, Eric Moulines
2013	—	`conf`	Surrogate Based Centralized SON: Application to Interference Mitigation in LTE-A HetNets. VTC Spring Yasir Khan, Berna Sayraç, Eric Moulines
2012	—	`conf`	An online learning algorithm for mixture models of deformable templates. MLSP Florian Maire, Sidonie Lefebvre, Randal Douc, Eric Moulines
2012	J	`jnl`	Detecting Aircraft With a Low-Resolution Infrared Sensor. IEEE Trans. Image Process. Jérémie Jakubowicz, Sidonie Lefebvre, Florian Maire, Eric Moulines
2012	—	`conf`	Improving coverage estimation for cellular networks with spatial bayesian prediction based on measurements. CellNet@SIGCOMM Berna Sayraç, Janne Riihijärvi, Petri Mähönen, Sana Ben Jemaa, Eric Moulines, Sebastien Grimoud
2012	—	`conf`	New Online EM Algorithms for General Hidden Markov Models. Application to the SLAM Problem. LVA/ICA Sylvain Le Corff, Gersende Fort, Eric Moulines
2012	—	`conf`	Sequential design of computer experiments for parameter estimation with application to numerical dosimetry. EUSIPCO Marjorie Jala, Céline Lévy-Leduc, Eric Moulines, Emmanuelle Conil, Joe Wiart
2011	—	`conf`	An algorithm for fast REM construction. CrownCom Sebastien Grimoud, Berna Sayraç, Sana Ben Jemaa, Eric Moulines
2011	—	`conf`	Best Sensor Selection for an Iterative REM Construction. VTC Fall Sebastien Grimoud, Berna Sayraç, Sana Ben Jemaa, Eric Moulines
2011	Misc	`conf`	CLT for eigen-inference methods in cognitive radios. ICASSP Jianfeng Yao, Romain Couillet, Jamal Najim, Eric Moulines, Mérouane Debbah
2011	J	`jnl`	Error Exponents for Neyman-Pearson Detection of a Continuous-Time Gaussian Markov Process From Regular or Irregular Samples. IEEE Trans. Inf. Theory Walid Hachem, Eric Moulines, François Roueff
2011	J	`jnl`	Inference of a Generalized Long Memory Process in the Wavelet Domain. IEEE Trans. Signal Process. Olaf Kouamo, Maurice Charbit, Eric Moulines, François Roueff
2011	—	`conf`	Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning. NIPS Francis R. Bach, Eric Moulines
2011	B	`conf`	On Upper-Confidence Bound Policies for Switching Bandit Problems. ALT Aurélien Garivier, Eric Moulines
2011	J	`jnl`	On adaptive stratification. Ann. Oper. Res. Pierre Etoré, Gersende Fort, Benjamin Jourdain, Eric Moulines
2010	C	`conf`	Detecting aircraft with a low resolution infrared sensor. IGARSS Jérémie Jakubowicz, Sidonie Lefebvre, Eric Moulines
2010	J	`jnl`	High-Rate Quantization for the Neyman-Pearson Detection of Hidden Markov Processes CoRR Joffrey Villard, Pascal Bianchi, Eric Moulines, Pablo Piantanida
2010	—	`conf`	Maximum likelihood blind deconvolution for sparse systems. CIP Steffen Barembruch, Anna Scaglione, Eric Moulines
2010	J	`jnl`	The expectation and sparse maximization algorithm. J. Commun. Networks Steffen Barembruch, Anna Scaglione, Eric Moulines
2009	J	`jnl`	Error exponents for Neyman-Pearson detection of a continuous-time Gaussian Markov process from noisy irregular samples CoRR Walid Hachem, Eric Moulines, François Roueff
2009	J	`jnl`	On approximate maximum-likelihood methods for blind identification: how to cope with the curse of dimensionality. IEEE Trans. Signal Process. Steffen Barembruch, Aurélien Garivier, Eric Moulines
2009	Misc	`conf`	On the error exponents for detecting randomly sampled noisy diffusion processes. ICASSP Walid Hachem, Eric Moulines, Jamal Najim, François Roueff
2008	—	`conf`	A Near Optimal Policy for Channel Allocation in Cognitive Radio. EWRL Sarah Filippi, Olivier Cappé, Fabrice Clérot, Eric Moulines
2008	—	`conf`	Adaptive methods for sequential importance sampling with application to state space models. EUSIPCO Julien Cornebise, Eric Moulines, Jimmy Olsson
2008	J	`jnl`	Adaptive methods for sequential importance sampling with application to state space models. Stat. Comput. Julien Cornebise, Eric Moulines, Jimmy Olsson
2008	B	`conf`	Informed spectrum usage in cognitive radio networks: Interference cartography. PIMRC Afef Ben Hadj Alaya-Feki, Sana Ben Jemaa, Berna Sayraç, Paul Houzé, Eric Moulines
2008	—	`conf`	Kernel Change-point Analysis. NIPS Zaïd Harchaoui, Francis R. Bach, Eric Moulines
2008	B	`conf`	Opportunistic Spectrum Access with IEEE 802.11 in IEEE P1900.4 Framework. WiMob Afef Ben Hadj Alaya-Feki, Berna Sayraç, Paul Houzé, Eric Moulines
2008	B	`conf`	Opportunistic Spectrum Access: Online Search of Optimality. GLOBECOM Afef Ben Hadj Alaya-Feki, Berna Sayraç, Eric Moulines, Alain Le Cornec
2008	—	`conf`	Semi Dynamic Parameter Tuning for Optimized Opportunistic Spectrum Access. VTC Fall Afef Ben Hadj Alaya-Feki, Berna Sayraç, Alain Le Cornec, Eric Moulines
2007	—	`conf`	A New Approach for Mobile Localization in Multipath Scenarios. ICC Nadir Castañeda, Maurice Charbit, Eric Moulines
2007	J	`jnl`	An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo. Proc. IEEE Olivier Cappé, Simon J. Godsill, Eric Moulines
2007	J	`jnl`	Online EM Algorithm for Latent Data Models CoRR Olivier Cappé, Eric Moulines
2007	J	`jnl`	Optimization of Radio Measurements Exploitation in Wireless Mobile Networks. J. Commun. Afef Ben Hadj Alaya-Feki, Alain Le Cornec, Eric Moulines
2007	J	`jnl`	Statistical Pileup Correction Method for HPGe Detectors. IEEE Trans. Signal Process. Thomas Trigano, Antoine Souloumiac, Thierry Montagu, François Roueff, Eric Moulines
2007	—	`conf`	Testing for Homogeneity with Kernel Fisher Discriminant Analysis. NIPS Zaïd Harchaoui, Francis R. Bach, Eric Moulines
2006	—	`conf`	Energy Spectrum Reconstruction for HPGe Detectors Using Analytical Pile-Up Correction. ICASSP (3) Thomas Trigano, François Roueff, Eric Moulines, Antoine Souloumiac, Thierry Montagu
2006	—	`conf`	ODE methods for Markov chain stability with applications to MCMC. VALUETOOLS Gersende Fort, Eric Moulines, Sean P. Meyn, Pierre Priouret
2006	—	`conf`	Recursive Em Algorithm with Applications to Doa Estimation. ICASSP (3) Olivier Cappé, Maurice Charbit, Eric Moulines
2006	—	`conf`	Source Localization from Quantized Time of Arrival Measurements. ICASSP (4) Nadir Castañeda, Maurice Charbit, Eric Moulines
2005	J	`jnl`	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. Marine Campedel, Eric Moulines
2005	J	`jnl`	Comparison of Resampling Schemes for Particle Filtering CoRR Randal Douc, Olivier Cappé, Eric Moulines
2005	—	`book`	Inference in hidden Markov models. Olivier Cappé, Eric Moulines, Tobias Rydén
2005	—	`conf`	Modeling, identification, and control of large-scale dynamical systems. ICASSP (5) Simon Haykin, Alfred O. Hero III, Eric Moulines
2005	—	`conf`	Méthodologie de sélection de caractéristiques pour la classification d'images satellitaires. CAP Marine Campedel, Eric Moulines
2005	—	`conf`	On the use of particle filtering for maximum likelihood parameter estimation. EUSIPCO Olivier Cappé, Eric Moulines
2005	—	`conf`	Stability of Stochastic Approximation under Verifiable Conditions. CDC/ECC Christophe Andrieu, Eric Moulines, Pierre Priouret
2005	J	`jnl`	Stability of Stochastic Approximation under Verifiable Conditions. SIAM J. Control. Optim. Christophe Andrieu, Eric Moulines, Pierre Priouret
2004	J	`jnl`	Global Sampling for Sequential Filtering over Discrete State Space. EURASIP J. Adv. Signal Process. Pascal Cheung-Mon-Chan, Eric Moulines
2003	J	`jnl`	A semi-blind channel estimation technique based on second-order blind method for CDMA systems. IEEE Trans. Signal Process. Samson Lasaulce, Philippe Loubaton, Eric Moulines
2002	J	`jnl`	Long-range dependence and heavy-tail modeling for teletraffic data. IEEE Signal Process. Mag. Olivier Cappé, Eric Moulines, Jean-Christophe Pesquet, Athina P. Petropulu, Xueshi Yang
2002	J	`jnl`	Semidefinite positive relaxation of the maximum-likelihood criterion applied to multiuser detection in a CDMA context. IEEE Signal Process. Lett. Moussa Abdi, Hassan El Nahas, Alexandre Jard, Eric Moulines
2001	Misc	`conf`	An adaptive broadband estimator of the fractional differencing coefficient. ICASSP Clifford M. Hurvich, Eric Moulines, Philippe Soulier
2001	J	`jnl`	Blind identification of multipath channels: a parametric subspace approach. IEEE Trans. Signal Process. Lisa Perros-Meilhac, Eric Moulines, Karim Abed-Meraim, Pascal Chevalier, Pierre Duhamel
2001	J	`jnl`	Estimation of the spectral envelope of voiced sounds using a penalized likelihood approach. IEEE Trans. Speech Audio Process. Marine Campedel-Oudot, Olivier Cappé, Eric Moulines
2001	—	`conf`	Training-based channel estimation and de-noising for the UMTS TDD mode. VTC Fall Samson Lasaulce, Philippe Loubaton, Eric Moulines, Soodesh Buljore
2000	J	`jnl`	In-variance of subspace based estimators. IEEE Trans. Signal Process. Jean-François Cardoso, Eric Moulines
2000	J	`jnl`	On a Perturbation Approach for the Analysis of Stochastic Tracking Algorithms. SIAM J. Control. Optim. Rafik Aguech, Eric Moulines, Pierre Priouret
2000	J	`jnl`	On blind multiuser forward link channel estimation by the subspace method: identifiability results. IEEE Trans. Signal Process. Philippe Loubaton, Eric Moulines
2000	J	`jnl`	On the performance of semi-blind subspace-based channel estimation. IEEE Trans. Signal Process. Vincent Buchoux, Olivier Cappé, Eric Moulines, Alexei Gorokhov
2000	Misc	`conf`	Performance of a subspace based semi-blind technique in the UMTS TDD mode context. ICASSP Samson Lasaulce, Philippe Loubaton, Eric Moulines
1999	J	`jnl`	A parametric blind subspace identification: robustness issue. IEEE Commun. Lett. Lisa Perros-Meilhac, Eric Moulines, Pascal Chevalier, Pierre Duhamel
1999	Misc	`conf`	Application of blind second order statistics MIMO identification methods to the blind CDMA forward link channel estimation. ICASSP Philippe Loubaton, Eric Moulines
1999	Misc	`conf`	Blind knowledge based algorithms based on second order statistics. ICASSP Lisa Perros-Meilhac, Pierre Duhamel, Pascal Chevalier, Eric Moulines
1999	J	`jnl`	Simulation-based methods for blind maximum-likelihood filter identification. Signal Process. Olivier Cappé, Arnaud Doucet, Marc Lavielle, Eric Moulines
1998	—	`conf`	A locally stationary semi-Markovian representation for ethernet LAN traffic data. Broadband Communications Sandrine Vaton, Eric Moulines
1998	J	`jnl`	An algorithm for maximum likelihood estimation of hidden Markov models with unknown state-tying. IEEE Trans. Speech Audio Process. Olivier Cappé, Chafic Mokbel, Denis Jouvet, Eric Moulines
1998	—	`conf`	Bayesian Analysis of Overdispersed Count Data with Application to Teletraffic Monitoring. COMPSTAT Olivier Cappé, Randal Douc, Eric Moulines, Christian P. Robert
1998	J	`jnl`	Blind and semi-blind equalization: methods and algorithms. Ann. des Télécommunications Vincent Buchoux, Lisa Perros-Meilhac, Olivier Cappé, Eric Moulines
1998	J	`jnl`	Continuous probabilistic transform for voice conversion. IEEE Trans. Speech Audio Process. Yannis Stylianou, Olivier Cappé, Eric Moulines
1998	Misc	`conf`	On a perturbation approach for the analysis of stochastic tracking algorithms. ICASSP Eric Moulines, Pierre Priouret, Rafik Aguech
1998	—	`conf`	On the Convergence of Iterated Random Maps with Applications to the MCEM Algorithm. COMPSTAT Gersende Fort, Eric Moulines, Philippe Soulier
1998	Misc	`conf`	Polynomial quasi-harmonic models for speech analysis and synthesis. ICASSP Gilles Faÿ, Eric Moulines, Olivier Cappé, Frédéric Bimbot
1998	Misc	`conf`	Quasi-Newton method for maximum likelihood estimation of hidden Markov models. ICASSP Olivier Cappé, Vincent Buchoux, Eric Moulines
1997	J	`jnl`	A blind source separation technique using second-order statistics. IEEE Trans. Signal Process. Adel Belouchrani, Karim Abed-Meraim, Jean-François Cardoso, Eric Moulines
1997	J	`jnl`	A simulated annealing version of the EM algorithm for non-Gaussian deconvolution. Stat. Comput. Marc Lavielle, Eric Moulines
1997	J	`jnl`	A subspace algorithm for certain blind identification problems. IEEE Trans. Inf. Theory Karim Abed-Meraim, Philippe Loubaton, Eric Moulines
1997	Misc	`conf`	Asymptotically invariant Gaussianity test for causal invertible time series. ICASSP Roxana Ojeda, Jean-François Cardoso, Eric Moulines
1997	Misc	`conf`	Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models. ICASSP Eric Moulines, Jean-François Cardoso, Elisabeth Gassiat
1997	J	`jnl`	On subspace methods for blind identification of single-input multiple-output FIR systems. IEEE Trans. Signal Process. Karim Abed-Meraim, Jean-François Cardoso, Alexei Y. Gorokhov, Philippe Loubaton, Eric Moulines
1997	J	`jnl`	Prediction error method for second-order blind identification. IEEE Trans. Signal Process. Karim Abed-Meraim, Eric Moulines, Philippe Loubaton
1996	J	`jnl`	Regularization techniques for discrete cepstrum estimation. IEEE Signal Process. Lett. Olivier Cappé, Eric Moulines
1996	Misc	`conf`	Second order blind equalization in multiple input multiple output FIR systems: a weighted least squares approach. ICASSP Alexei Gorokhov, Philippe Loubaton, Eric Moulines
1996	Misc	`conf`	Subspace methods for blind identification of SIMO-FIR systems. ICASSP Eric Moulines, Jean-François Cardoso, Alexei Gorokhov, Philippe Loubaton
1996	J	`jnl`	Time-domain procedures for testing that a stationary time-series is Gaussian. IEEE Trans. Signal Process. Eric Moulines, Karim Choukri
1995	J	`jnl`	Asymptotic performance analysis of direction-finding algorithms based on fourth-order cumulants. IEEE Trans. Signal Process. Jean-François Cardoso, Eric Moulines
1995	J	`jnl`	Editorial. Speech Commun. Eric Moulines, Yoshinori Sagisaka
1995	—	`conf`	High-quality speech modification based on a harmonic + noise model. EUROSPEECH Yannis Stylianou, Jean Laroche, Eric Moulines
1995	J	`jnl`	Non-parametric techniques for pitch-scale and time-scale modification of speech. Speech Commun. Eric Moulines, Jean Laroche
1995	Misc	`conf`	Prediction error methods for time-domain blind identification of multichannel FIR filters. ICASSP Karim Abed-Meraim, Pierre Duhamel, David Gesbert, Philippe Loubaton, Sylvie Mayrargue, Eric Moulines, Dirk T. M. Slock
1995	—	`conf`	Statistical methods for voice quality transformation. EUROSPEECH Yannis Stylianou, Olivier Cappé, Eric Moulines
1995	J	`jnl`	Subspace methods for the blind identification of multichannel FIR filters. IEEE Trans. Signal Process. Eric Moulines, Pierre Duhamel, Jean-François Cardoso, Sylvie Mayrargue
1995	J	`jnl`	The generalized multidelay adaptive filter: structure and convergence analysis. IEEE Trans. Signal Process. Eric Moulines, Omar Ait Amrane, Yves Grenier
1994	J	`jnl`	A robustness property of DOA estimators based on covariance. IEEE Trans. Signal Process. Jean-François Cardoso, Eric Moulines
1994	—	`conf`	Asymptotic performance of second order blind separation. ICASSP (4) Karim Abed-Meraim, Adel Belouchrani, Jean-François Cardoso, Eric Moulines
1994	—	`conf`	Subspace methods for the blind identification of multichannel FIR filters. ICASSP (4) Eric Moulines, Pierre Duhamel, Jean-François Cardoso, Sylvie Mayrargue
1993	—	`conf`	HNS: Speech modification based on a harmonic+noise model. ICASSP (2) Jean Laroche, Yannis Stylianou, Eric Moulines
1993	—	`conf`	Minimum constrast estimation with applications to array processing. ICASSP (4) Jean-François Cardoso, Eric Moulines
1992	Misc	`conf`	Direction finding algorithms using fourth order statistics: asymptotic performance analysis. ICASSP Eric Moulines, Jean-François Cardoso
1992	Misc	`conf`	Low-delay frequency domain LMS algorithm. ICASSP Omar Ait Amrane, Eric Moulines, Maurice Charbit, Yves Grenier
1992	J	`jnl`	Voice transformation using PSOLA technique. Speech Commun. Hélène Valbret, Eric Moulines, Jean-Pierre Tubach
1991	—	`conf`	Voice tranformation using PSOLA technique. EUROSPEECH Hélène Valbret, Eric Moulines, Jean-Pierre Tubach
1990	Misc	`conf`	A real-time French text-to-speech system generating high-quality synthetic speech. ICASSP Eric Moulines, Françoise Emerard, Danielle Larreur, J. L. Le Saint-Milon, L. Le Faucheur, F. Marty, Francis Charpentier, Christel Sorin
1990	J	`jnl`	Detection of the glottal closure by jumps in the statistical properties of the speech signal. Speech Commun. Eric Moulines, Renaud J. Di Francesco
1990	J	`jnl`	Pitch-synchronous waveform processing techniques for text-to-speech synthesis using diphones. Speech Commun. Eric Moulines, Francis Charpentier
1989	Misc	`conf`	A diphone synthesis system based on time-domain prosodic modifications of speech. ICASSP Christian Hamon, Eric Moulines, Francis Charpentier
1989	—	`conf`	Detection of the glottal closure by jumps in the statistical properties of the signal. EUROSPEECH Renaud J. Di Francesco, Eric Moulines
1989	—	`conf`	Pitch-synchronous waveform processing techniques for text-to-speech synthesis using diphones. EUROSPEECH Francis Charpentier, Eric Moulines
1988	Misc	`conf`	Text-to-speech algorithms based on FFT synthesis. ICASSP Francis Charpentier, Eric Moulines
1987	—	`conf`	Text-to-speech synthesis in the French electronic mail environment. ECST Christel Sorin, Raymond Descout, Christian Benoît, Françoise Emerard, C. Fluhr, Danielle Larreur, J. L. Le Saint-Milon, Eric Moulines, R. Peron