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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
Posts
SCAI workshop Machine learning and AI to analyze gut microbiota
Co-organized with Anna Bonnet and Harry Sokol
Hi! PARIS webinar “AI for the energy transition”
Co-organized with Anne-Laure Sellier
- Damien Ernst – ULiège and Hi! PARIS Chair at Télécom Paris, IP Paris
- Sam Aflaki – HEC Paris, Department Chair and Associate Professor of Operations Management
- Victor Martin – TotalEnergies, Head of numeric platform for power and sustainability R&D
CIRM Winter school “End-to-end Bayesian learning”
Co-organized with Julien Stoehr and Pierre Gloaguen
Hi! PARIS webinar “AI for sustainability”
Co-organized with Anne-Laure Sellier
- Philippe Drobinski – Ecole Polytechnique / Director of Energy4Climate
- Julien Grand-Clement – HEC Paris
- Peter Tankov – ENSAE
Hi! PARIS webinar “AI healthcare”
Co-organized with Anne-Laure Sellier
- Catalin Fetita Telecom SudParis
- Marc Lavielle – INRIA
- Adriana Tapus – ENSTA Paris
- Gael Varoquaux – INRIA
Hi! PARIS webinar “Bias and data privacy”
Co-organized with Anne-Laure Sellier
- Christophe Perignon – HEC Paris
- Stephan Clemencon – Telecom Paris
- Ruslan Momot – HEC Paris
- Catuscia Palamidessi – Ecole Polytechnique
publications
Cyrille Dubarry & Sylvain Le Corff (2011). " Fast computation of smoothed additive functionals in general state-space models." IEEE Workshop on Statistical Signal Processing (SSP), 197-200
Sylvain Le Corff, Gersende Fort & Eric Moulines (2011). " Online Expectation Maximization based algorithms for inference in hidden Markov models." IEEE Workshop on Statistical Signal Processing (SSP), 225-228
Thierry Dumont & Sylvain Le Corff (2013). " Online EM for indoor simultaneous localization and mapping." IEEE International Conference on Acoustics, Speech and Signal Processing 6431-6435
Cyrille Dubarry & Sylvain Le Corff (2013). " Nonasymptotic deviation inequalities for smoothed additive functionals in nonlinear state-space models with applications to parameter estimation." Bernoulli 19(5B):2222-2249
Sylvain Le Corff & Gersende Fort (2013). " Online Expectation Maximization based algorithms for inference in hidden Markov models." Electronic Journal of Statistics, 7(5B):763-792
Sylvain Le Corff & Gersende Fort (2013). " Convergence of a Particle-Based Approximation of the Block Online Expectation Maximization Algorithm." ACM Transactions on Modeling and Computer Simulation, 23(1):1-22
Sylvain Le Corff, Gersende Fort & Eric Moulines (2013). " New Online EM algorithms for general hidden Markov models. Application to the SLAM problem." Proceedings of the 10th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA) 131:138
Thierry Dumont & Sylvain Le Corff (2014). " Simultaneous localization and mapping in wireless sensor networks." Signal Processing, 101:192-203
Amandine Schreck, Gersende Fort, Sylvain Le Corff & Eric Moulines (2015). " A Shrinkage-Thresholding Metropolis Adjusted Langevin Algorithm for Bayesian Variable Selection." IEEE Journal of Selected Topics in Signal Processing, 10:366-375
Yohann de Castro, Sylvain Le Corff & Elisabeth Gassiat (2017). " Consistent estimation of the filtering and marginal smoothing distributions in nonparametric hidden Markov models." IEEE Transactions on Information Theory, 63(8):4758-4777
Rainer Dahlhaus, Thierry Dumont, Sylvain Le Corff & Jan C. Neddermeyer (2017). " Statistical Inference for Oscillation Processes." Statistics, 51(1):61-83
Thierry Dumont & Sylvain Le Corff (2017). " Nonparametric regression on hidden Φ-mixing variables: Identifiability and consistency of a pseudo-likelihood based estimation procedure." Bernoulli, 23(2):990-1021
Alain Durmus, Sylvain Le Corff, Eric Moulines & Gareth O. Roberts (2017). " Optimal scaling of the random walk Metropolis algorithm under Lp mean differentiability." Journal of Applied Probability, 54(4):1233-1260
Thi Ngoc Minh Nguyen, Sylvain Le Corff & Eric Moulines (2017). " Particle rejuvenation of Rao-Blackwellized Sequential Monte Carlo smoothers for Conditionally Linear and Gaussian models." EURASIP Journal on Advances in Signal Processing, 54
Pierre Gloaguen, Marie-Pierre Etienne and Sylvain Le Corff (2018). " Stochastic Differential Equation Based on a Multimodal Potential to Model Movement Data in Ecology." Journal of the Royal Statistical Society: Series C, 67(3):599-616
Pierre Gloaguen, Marie-Pierre Etienne & Sylvain Le Corff (2018). " Online sequential Monte Carlo smoother for partially observed diffusion processes." EURASIP Journal on Advances in Signal Processing, 9
Thi Ngoc Minh Nguyen, Sylvain Le Corff & Eric Moulines (2018). " On the two-filter approximations of marginal smoothing distributions in general state-space models." Advances in Applied Probability, 50(1):154-177
Roland Diel, Sylvain Le Corff & Matthieu Lerasle (2020). " Learning the distribution of latent variables in paired comparison models with round-robin scheduling." Bernoulli, 26(4):2670-2698
Elisabeth Gassiat, Sylvain Le Corff & Luc Lehéricy (2020). " Identifiability and consistent estimation of nonparametric translation hidden Markov models with general state space." The Journal of Machine Learning Research, 115:1-40
Sylvain Le Corff, Matthieu Lerasle & Elodie Vernet (2020). " A Bayesian nonparametric approach for generalized Bradley-Terry models in random environment."
Hermanni Hälvä, Sylvain Le Corff, Luc Lehéricy, Jonathan So, Yongjie Zhu, Elisabeth Gassiat & Aapo Hyvarinen (2021). " Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA." Advances in Neural Information Processing Systems 34 (NeurIPS), 34:1624-1633
Achille Thin, Yazid Janati El Idrissi, Sylvain Le Corff, Charles Ollion, Eric Moulines, Arnaud Doucet, Alain Durmus & Christian P. Robert (2021). " NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform." Advances in Neural Information Processing Systems 34 (NeurIPS), 34:17060-17071
Elisabeth Gassiat, Sylvain Le Corff & Luc Lehericy (2022). "Deconvolution with unknown noise distribution is possible for multivariate signals." The Annals of Statistics, 50(1):303-323
Alice Martin, Guillaume Quispe, Charles Ollion, Sylvain Le Corff, Florian Strub & Olivier Pietquin (2022). " Learning Natural Language Generation with Truncated Reinforcement Learning." Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), 12:37
Max Cohen, Guillaume Quispe, Sylvain Le Corff, Charles Ollion & Eric Moulines (2022). "Diffusion bridges vector quantized variational autoencoders." Proceedings of the 39th International Conference on Machine Learning (ICML), PMLR 162:4141-4156.
Pierre Gloaguen, Sylvain Le Corff & Jimmy Olsson (2022). " A pseudo-marginal sequential Monte Carlo online smoothing algorithm." Bernoulli, 28(4):2606-2633.
Alice Martin, Marie-Pierre Étienne, Pierre Gloaguen, Sylvain Le Corff & Jimmy Olsson (2023). " Backward importance sampling for online estimation of state space models." Journal of Computational and Graphical Statistics, 32(4):1447-1460
Gabriel Cardoso, Yazid Janati, Sylvain Le Corff, Eric Moulines & Jimmy Olsson (2023). " State and parameter learning with PaRISian Particle Gibbs." Proceedings of the 40th International Conference on Machine Learning (ICML), PMLR 202:3625-3675.
Mathis Chagneux, Élisabeth Gassiat, Pierre Gloaguen & Sylvain Le Corff (2023). " Additive smoothing error in backward variational inference for general state-space models." To appear in The Journal of Machine Learning Research
Etienne David, Jean Bellot & Sylvain Le Corff (2023). " HERMES: Hybrid Error-corrector Model with inclusion of External Signals for nonstationary time series." Transactions on Machine Learning Research
Yazid Janati, Sylvain Le Corff & Yohan Petetin (2023). " Variance estimation for Sequential Monte Carlo Algorithms: a backward sampling approach." To appear in Bernoulli
Randal Douc & Sylvain Le Corff (2023). "Asymptotic convergence of iterative optimization algorithms." Under review
Etienne David, Jean Bellot, Sylvain Le Corff & Luc Lehericy (2024). " Identifiability of discrete Input-output hidden Markov models with external signals." Statistics and Computing, 34(54).
Gabriel Cardoso, Yazid Janati El Idrissi, Sylvain Le Corff & Eric Moulines (2024). "Monte Carlo guided Diffusion for Bayesian linear inverse problems." Under review
Elisabeth Gassiat & Sylvain Le Corff (2024). "Variational excess risk bound for general state space models." Under review