Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere A Thomas, S Clémençon, A Gramfort, A Sabourin
Proceedings of the 20th International Conference on Artificial Intelligence …, 2017
21 2017 Mass volume curves and anomaly ranking S Clémençon, A Thomas
Electronic Journal of Statistics 12 (2), 2806-2872, 2018
20 2018 Calibration of One-Class SVM for MV set estimation A Thomas, V Feuillard, A Gramfort
Data Science and Advanced Analytics (DSAA), 2015. 36678 2015. IEEE …, 2015
20 2015 Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose? B Kégl, G Hurtado, A Thomas
International Conference on Learning Representations, 2020
15 2020 Learning Hyperparameters for Unsupervised Anomaly Detection. A Thomas, S Clémençon, V Feuillard, A Gramfort
12 2016 Parallel Contextual Bandits in Wireless Handover Optimization I Colin, A Thomas, M Draief
2018 IEEE International Conference on Data Mining Workshops (ICDMW), 258-265, 2018
11 2018 Best Arm Identification in Graphical Bilinear Bandits G Rizk, A Thomas, I Colin, R Laraki, Y Chevaleyre
International Conference on Machine Learning, 9010-9019, 2021
7 2021 Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level A Grosnit, A Maraval, J Doran, G Paolo, A Thomas, RSHN Beevi, ...
arXiv preprint arXiv:2411.03562, 2024
6 2024 Guided Safe Shooting: model based reinforcement learning with safety constraints G Paolo, J Gonzalez-Billandon, A Thomas, B Kégl
arXiv preprint arXiv:2206.09743, 2022
4 2022 Refined bounds for randomized experimental design G Rizk, I Colin, A Thomas, M Draief
arXiv preprint arXiv:2012.15726, 2020
3 2020 Zero-shot Model-based Reinforcement Learning using Large Language Models A Benechehab, YAE Hili, A Odonnat, O Zekri, A Thomas, G Paolo, ...
arXiv preprint arXiv:2410.11711, 2024
2 2024 Multi-timestep models for Model-based Reinforcement Learning A Benechehab, G Paolo, A Thomas, M Filippone, B Kégl
arXiv preprint arXiv:2310.05672, 2023
1 2023 AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting A Benechehab, V Feofanov, G Paolo, A Thomas, M Filippone, B Kégl
arXiv preprint arXiv:2502.10235, 2025
2025 Differentially Private Model-Based Offline Reinforcement Learning A Rio, M Barlier, I Colin, A Thomas
arXiv preprint arXiv:2402.05525, 2024
2024 A Multi-step Loss Function for Robust Learning of the Dynamics in Model-based Reinforcement Learning A Benechehab, A Thomas, G Paolo, M Filippone, B Kégl
arXiv preprint arXiv:2402.03146, 2024
2024 Deep autoregressive density nets vs neural ensembles for model-based offline reinforcement learning A Benechehab, A Thomas, B Kégl
arXiv preprint arXiv:2402.02858, 2024
2024 Fair Model-Based Reinforcement Learning Comparisons with Explicit and Consistent Update Frequency A Thomas, A Benechehab, G Paolo, B Kégl
The Third Blogpost Track at ICLR 2024, 2024
2024 An G Rizk, I Colin, A Thomas, R Laraki, Y Chevaleyre
Advances in Neural Information Processing Systems 35, 19113-19123, 2022
2022 Differentially Private Deep Model-Based Reinforcement Learning A Rio, M Barlier, I Colin, A Thomas
Seventeenth European Workshop on Reinforcement Learning, 0
A Study of the Weighted Multi-step Loss Impact on the Predictive Error and the Return in MBRL A Benechehab, A Thomas, G Paolo, M Filippone, B Kégl
I Can't Believe It's Not Better Workshop: Failure Modes of Sequential …, 0
Alexandre GramfortMetaبريد إلكتروني تم التحقق منه على meta.com