| Online estimation of the geometric median in Hilbert spaces: Nonasymptotic confidence balls H Cardot, P Cénac, A Godichon-Baggioni | 66 | 2017 |
| Clustering transformed compositional data using K-means, with applications in gene expression and bicycle sharing system data A Godichon-Baggioni, C Maugis-Rabusseau, A Rau Journal of Applied Statistics 46 (1), 47-65, 2019 | 49 | 2019 |
| Estimating the geometric median in Hilbert spaces with stochastic gradient algorithms: Lp and almost sure rates of convergence A Godichon-Baggioni Journal of Multivariate Analysis 146, 209-222, 2016 | 46 | 2016 |
| Fast estimation of the median covariation matrix with application to online robust principal components analysis H Cardot, A Godichon-Baggioni Test 26 (3), 461-480, 2017 | 33* | 2017 |
| An efficient stochastic newton algorithm for parameter estimation in logistic regressions B Bercu, A Godichon, B Portier SIAM Journal on Control and Optimization 58 (1), 348-367, 2020 | 27 | 2020 |
| On the asymptotic rate of convergence of stochastic newton algorithms and their weighted averaged versions C Boyer, A Godichon-Baggioni Computational Optimization and Applications 84 (3), 921-972, 2023 | 22 | 2023 |
| On the rates of convergence of parallelized averaged stochastic gradient algorithms A Godichon-Baggioni, S Saadane Statistics 54 (3), 618-635, 2020 | 21 | 2020 |
| Lp and almost sure rates of convergence of averaged stochastic gradient algorithms: locally strongly convex objective A Godichon-Baggioni ESAIM: Probability and Statistics 23, 841-873, 2019 | 19* | 2019 |
| Online estimation of the asymptotic variance for averaged stochastic gradient algorithms A Godichon-Baggioni Journal of Statistical Planning and Inference 203, 1-19, 2019 | 15* | 2019 |
| An efficient averaged stochastic Gauss-Newton algorithm for estimating parameters of non linear regressions models P Cénac, A Godichon-Baggioni, B Portier arXiv preprint arXiv:2006.12920, 2020 | 13 | 2020 |
| 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 | 8 | 2023 |
| An averaged projected robbins-monro algorithm for estimating the parameters of a truncated spherical distribution A Godichon-Baggioni, B Portier | 8 | 2017 |
| Recursive ridge regression using second-order stochastic algorithms A Godichon-Baggioni, W Lu, B Portier | 5 | 2022 |
| Learning from time-dependent streaming data with online stochastic algorithms A Godichon-Baggioni, N Werge, O Wintenberger arXiv preprint arXiv:2205.12549, 2022 | 5 | 2022 |
| A robust model-based clustering based on the geometric median and the median covariation matrix A Godichon-Baggioni, S Robin Statistics and Computing 34 (1), 55, 2024 | 4 | 2024 |
| Convergence in quadratic mean of averaged stochastic gradient algorithms without strong convexity nor bounded gradient A Godichon-Baggioni Statistics 57 (3), 637-668, 2023 | 4 | 2023 |
| Non asymptotic analysis of Adaptive stochastic gradient algorithms and applications A Godichon-Baggioni, P Tarrago arXiv preprint arXiv:2303.01370, 2023 | 4 | 2023 |
| Online stochastic newton methods for estimating the geometric median and applications A Godichon-Baggioni, W Lu arXiv preprint arXiv:2304.00770, 2023 | 3 | 2023 |
| coseq A Rau, CM Rabusseau, A Godichon-Baggioni | 2 | 2017 |
| A penalized criterion for selecting the number of clusters for K-medians A Godichon-Baggioni, S Surendran Journal of Computational and Graphical Statistics, 1-25, 2024 | 1 | 2024 |
Andrea RauSenior research scientist, INRAEVerified email at inrae.fr
