Publications de Matthieu JONCKHEERE
Elene Anton, Urtzi Ayesta, Matthieu Jonckheere, Ina Maria Maaike Verloop
On the stability of redundancy models
Operations Research, 2021, 69 (5), pp.1540-1565. ⟨10.1287/opre.2020.2030⟩
Elene Anton, Urtzi Ayesta, Matthieu Jonckheere, Ina Maria Maaike Verloop
Improving the performance of heterogeneous data centers through redundancy
Proceedings of the ACM on Measurement and Analysis of Computing Systems , 2020, 4 (3), pp.1-29. ⟨10.1145/3428333⟩
Urtzi Ayesta, Martin Erausquin, Matthieu Jonckheere, Maaike Verloop
Scheduling in a random environment: stability and asymptotic optimality
Dans : IEEE/ACM Transactions on Networking, IEEE : Institute of Electrical and Electronics Engineers, Vol. 21 N. 1, p. 258-271, février 2013.
Accès : http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06209453 – https://oatao.univ-toulouse.fr/12319/
BibTeX
Daniel Mastropietro, Szymon Majewski, Urtzi Ayesta, Matthieu Jonckheere
Boosting reinforcement learning with sparse and rare rewards using Fleming-Viot particle systems
15th European Workshop on Reinforcement Learning (EWRL 2022), Sep 2022, Milano, Italy
Elene Anton, Urtzi Ayesta, Matthieu Jonckheere, Ina Maria Maaike Verloop
A Survey of Stability Results for Redundancy Systems
Alexey Piunovskiy; Yi Zhang. Modern Trends in Controlled Stochastic Processes : Theory and Applications, Volume III, 41, Springer, pp.266-283, 2021, Emergence, Complexity and Computation (ECC), 978-3-030-76927-7. ⟨10.1007/978-3-030-76928-4_13⟩
Céline Comte, Matthieu Jonckheere, Jaron Sanders, Albert Senen-Cerda
Score-Aware Policy-Gradient Methods and Performance Guarantees using Local Lyapunov Conditions
2024
Daniel Mastropietro, Urtzi Ayesta, Matthieu Jonckheere, Szymon Majewski
Efficient reinforcement learning with Fleming-Viot particle systems: application to stochastic networks with rarely observed rewards
2023