| Self-training: A survey MR Amini, V Feofanov, L Pauletto, L Hadjadj, E Devijver, Y Maximov Neurocomputing 616, 128904, 2025 | 153* | 2025 |
| Wrapper feature selection with partially labeled data V Feofanov, E Devijver, MR Amini Applied Intelligence 52 (11), 12316-12329, 2022 | 33* | 2022 |
| Transductive bounds for the multi-class majority vote classifier V Feofanov, E Devijver, MR Amini Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3566-3573, 2019 | 27 | 2019 |
| Samformer: Unlocking the potential of transformers in time series forecasting with sharpness-aware minimization and channel-wise attention R Ilbert, A Odonnat, V Feofanov, A Virmaux, G Paolo, T Palpanas, I Redko arXiv preprint arXiv:2402.10198, 2024 | 17* | 2024 |
| Leveraging ensemble diversity for robust self-training in the presence of sample selection bias A Odonnat, V Feofanov, I Redko International Conference on Artificial Intelligence and Statistics, 595-603, 2024 | 7 | 2024 |
| Multi-class probabilistic bounds for majority vote classifiers with partially labeled data V Feofanov, E Devijver, MR Amini Journal of Machine Learning Research 25 (104), 1-47, 2024 | 7* | 2024 |
| Random matrix analysis to balance between supervised and unsupervised learning under the low density separation assumption V Feofanov, M Tiomoko, A Virmaux International Conference on Machine Learning, 10008-10033, 2023 | 6 | 2023 |
| User-friendly Foundation Model Adapters for Multivariate Time Series Classification V Feofanov, R Ilbert, M Tiomoko, T Palpanas, I Redko arXiv preprint arXiv:2409.12264, 2024 | 1 | 2024 |
| Enhancing multivariate time series forecasting via multi-task learning and random matrix theory R Ilbert, M Tiomoko, C Louart, V Feofanov, T Palpanas, I Redko NeurIPS Workshop on Time Series in the Age of Large Models, 2024 | 1 | 2024 |
| Characterising Gradients for Unsupervised Accuracy Estimation under Distribution Shift R Xie, A Odonnat, V Feofanov, I Redko, J Zhang, B An arXiv e-prints, arXiv: 2401.08909, 2024 | 1 | 2024 |
| Пошаговая дискриминация, кросс-валидация и бутстрап в задаче классификации пострадавших с сочетанной травмой груди ВА Феофанов Процессы управления и устойчивость 3 (1), 327-331, 2016 | 1 | 2016 |
| 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 |
| Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting R Ilbert, M Tiomoko, C Louart, A Odonnat, V Feofanov, T Palpanas, ... Advances in Neural Information Processing Systems 37, 115021-115057, 2025 | | 2025 |
| Measuring Pre-training Data Quality without Labels for Time Series Foundation Models S Wen, V Feofanov, J Zhang arXiv preprint arXiv:2412.06368, 2024 | | 2024 |
| MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts R Xie, A Odonnat, V Feofanov, W Deng, J Zhang, B An arXiv preprint arXiv:2405.18979, 2024 | | 2024 |
| Learning with Partially Labeled Data for Multi-class Classification and Feature Selection V Feofanov Université Grenoble Alpes [2020-....], 2021 | | 2021 |
| Bornes du vote majoritaire multi-classes en présence du bruit sur les étiquettes de classes V Feofanov, E Devijver, MR Amini Conférence sur l'Apprentissage Automatique, 2021 | | 2021 |
| Дискриминантный анализ базы данных ВА Феофанов | | |
Massih-Reza AminiProfessor, University Grenoble AlpesПодтвержден адрес электронной почты в домене imag.fr
