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ORCIDVincent Plassier
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2020 – today
- 2024
[c5]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- [i8]Vincent Plassier, Alexander Fishkov, Maxim Panov, Eric Moulines:
Conditionally valid Probabilistic Conformal Prediction. CoRR abs/2407.01794 (2024) - 2023
- [c4]Vincent Plassier, Eric Moulines, Alain Durmus:
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms. AISTATS 2023: 5299-5356 - [c3]Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov:
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. ICML 2023: 27907-27947 - [i7]Vincent Plassier, Mehdi Makni, Aleksandr Rubashevskii, Eric Moulines, Maxim Panov:
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift. CoRR abs/2306.05131 (2023) - [i6]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
- [c2]Maxime Vono, Vincent Plassier, Alain Durmus, Aymeric Dieuleveut, Eric Moulines:
QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning. AISTATS 2022: 6459-6500 - [i5]Hamid Jalalzai, Elie Kadoche, Rémi Leluc, Vincent Plassier:
Membership Inference Attacks via Adversarial Examples. CoRR abs/2207.13572 (2022) - [i4]Vincent Plassier, Alain Durmus, Eric Moulines:
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms. CoRR abs/2211.00100 (2022) - 2021
- [c1]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 - [i3]Maxime Vono, Vincent Plassier, Alain Durmus, Aymeric Dieuleveut, Eric Moulines:
QLSD: Quantised Langevin stochastic dynamics for Bayesian federated learning. CoRR abs/2106.00797 (2021) - [i2]Vincent Plassier, Maxime Vono, Alain Durmus, Eric Moulines:
DG-LMC: A Turn-key and Scalable Synchronous Distributed MCMC Algorithm. CoRR abs/2106.06300 (2021) - 2020
- [i1]Vincent Plassier, François Portier, Johan Segers:
Risk bounds when learning infinitely many response functions by ordinary linear regression. CoRR abs/2006.09223 (2020)
Coauthor Index
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