Personal profile
Personal profile
Since November 2022, she has been a part-time researcher at ENSTA Paris, within the Unité d'Informatique et d'Ingénierie des Systèmes (U2IS).
From September 2019 to October 2022, she was a Ph.D. student under the supervision of Francis Bach. During this time, she worked in the SIERRA team in Paris, a joint team between Inria Paris, ENS Paris, and CNRS. Her research focused on developing efficient algorithms for optimal control and reinforcement learning, with a particular interest in methods applicable to robotics and supported by theoretical guarantees.
Prior to that, she worked in the MLO team under the supervision of Martin Jaggi, focusing on privacy-preserving machine learning.
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Collaborations and top research areas from the last five years
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Enhancing Concept Localization in CLIP-based Concept Bottleneck Models
Kazmierczak, R., Azzolin, S., Berthier, E., Frehse, G. & Franchi, G., 1 Jan 2026, In: Transactions on Machine Learning Research. 2026-JanuaryResearch output: Contribution to journal › Article › peer-review
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Time-Varying Gaussian Process Bandit Optimization with Experts: No-Regret in Logarithmically-Many Side Queries
Mauduit, E., Berthier, E. & Simonetto, A., 1 Jan 2026, Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Proceedings. Ribeiro, R. P., Soares, C., Gama, J., Pfahringer, B., Japkowicz, N., Larrañaga, P., Jorge, A. M. & Abreu, P. H. (eds.). Springer Science and Business Media Deutschland GmbH, p. 164-182 19 p. (Lecture Notes in Computer Science; vol. 16017 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Explainability and vision foundation models: A survey
Kazmierczak, R., Berthier, E., Frehse, G. & Franchi, G., 1 Oct 2025, In: Information Fusion. 122, 103184.Research output: Contribution to journal › Article › peer-review
Open Access -
CLIP-QDA: An Explainable Concept Bottleneck Model
Kazmierczak, R., Berthier, E., Frehse, G. & Franchi, G., 1 Jan 2024, In: Transactions on Machine Learning Research. 2024Research output: Contribution to journal › Article › peer-review
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ON DOUBLE DESCENT IN REINFORCEMENT LEARNING WITH LSTD AND RANDOM FEATURES
Brellmann, D., Berthier, E., Filliat, D. & Frehse, G., 1 Jan 2024.Research output: Contribution to conference › Paper › peer-review
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A Non-asymptotic Analysis of Non-parametric Temporal-Difference Learning
Berthier, E., Kobeissi, Z. & Bach, F., 1 Jan 2022, Advances in Neural Information Processing Systems 35 - 36th Conference on Neural Information Processing Systems, NeurIPS 2022. Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 35).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Infinite-Dimensional Sums-of-Squares for Optimal Control
Berthier, E., Carpentier, J., Rudi, A. & Bach, F., 1 Jan 2022, 2022 IEEE 61st Conference on Decision and Control, CDC 2022. Institute of Electrical and Electronics Engineers Inc., p. 577-582 6 p. (Proceedings of the IEEE Conference on Decision and Control; vol. 2022-December).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
Fast and Robust Stability Region Estimation for Nonlinear Dynamical Systems
Berthier, E., Carpentier, J. & Bach, F., 1 Jan 2021, 2021 European Control Conference, ECC 2021. Institute of Electrical and Electronics Engineers Inc., p. 1412-1419 8 p. (2021 European Control Conference, ECC 2021).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Max-Plus Linear Approximations for Deterministic Continuous-State Markov Decision Processes
Berthier, E. & Bach, F., 1 Jul 2020, In: IEEE Control Systems Letters. 4, 3, p. 767-772 6 p., 8993726.Research output: Contribution to journal › Article › peer-review
Open Access