| AdaVol: An Adaptive Recursive Volatility Prediction Method N Werge, O Wintenberger Econometrics and Statistics 23, 19-35, 2022 | 11 | 2022 |
| Non-asymptotic analysis of stochastic approximation algorithms for streaming data A Godichon-Baggioni, N Werge, O Wintenberger ESAIM: Probability and Statistics 27, 482-514, 2023 | 10 | 2023 |
| Learning from time-dependent streaming data with online stochastic algorithms A Godichon-Baggioni, N Werge, O Wintenberger Transactions on Machine Learning Research, 2023 | 7 | 2023 |
| On Adaptive Stochastic Optimization for Streaming Data: A Newton's Method with O(dN) Operations A Godichon-Baggioni, N Werge arXiv preprint arXiv:2311.17753, 2023 | 5 | 2023 |
| Predicting risk-adjusted returns using an asset independent regime-switching model N Werge Expert Systems with Applications 184, 115576, 2021 | 5 | 2021 |
| An adaptive volatility method for probabilistic forecasting and its application to the M6 financial forecasting competition J de Vilmarest, N Werge International Journal of Forecasting, 2024 | 1 | 2024 |
| Exploring Pessimism and Optimism Dynamics in Deep Reinforcement Learning B Tasdighi, N Werge, YS Wu, M Kandemir arXiv preprint arXiv:2406.03890, 2024 | | 2024 |
| Deep Exploration with PAC-Bayes B Tasdighi, M Haussmann, N Werge, YS Wu, M Kandemir arXiv preprint arXiv:2402.03055, 2024 | | 2024 |
| BOF-UCB: A Bayesian-Optimistic Frequentist Algorithm for Non-Stationary Contextual Bandits N Werge, A Akgül, M Kandemir arXiv preprint arXiv:2307.03587, 2023 | | 2023 |
| Learning from time-dependent streaming data with online stochastic algorithms N Werge Sorbonne Université, 2022 | | 2022 |
| Online prediction of the volatility of high-frequency financial data N Werge Department of Mathematical Sciences, University of Copenhagen, 2016 | | 2016 |
Olivier WintenbergerLPSM, Sorbonne UniversityAdresă de e-mail confirmată pe upmc.fr