| Multi-Domain Adversarial Learning AS Sebag, L Heinrich, M Schoenauer, M Sebag, L Wu, S Altschuler ICLR'19-Seventh annual International Conference on Learning Representations, 2019 | 73* | 2019 |
| A generic methodological framework for studying single cell motility in high-throughput time-lapse data A Schoenauer Sebag, S Plancade, C Raulet-Tomkiewicz, R Barouki, ... Bioinformatics 31 (12), i320-i328, 2015 | 25 | 2015 |
| Stochastic gradient descent: Going as fast as possible but not faster A Schoenauer Sebag, M Schoenauer, M Sebag OPTML 2017: 10th NIPS Workshop on Optimization for Machine Learning, 1-8, 2017 | 13 | 2017 |
| What 3.5 million French firms can tell us about the efficiency of Covid-19 support measures B Coeuré | 10 | 2021 |
| Infering an ontology of single cell motions from high-throughput microscopy data AS Sebag, S Plancade, C Raulet-Tomkiewicz, R Barouki, JP Vert, ... 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 160-163, 2015 | 5 | 2015 |
| A Keyword Based Approach to Understanding the Overpenalization of Marginalized Groups by English Marginal Abuse Models on Twitter K Yee, AS Sebag, O Redfield, E Sheng, M Eck, L Belli arXiv preprint arXiv:2210.06351, 2022 | 3 | 2022 |
| Introducing v0. 5 of the AI Safety Benchmark from MLCommons B Vidgen, A Agrawal, AM Ahmed, V Akinwande, N Al-Nuaimi, N Alfaraj, ... arXiv preprint arXiv:2404.12241, 2024 | | 2024 |
| Assessing Online True Threats And Their Impacts: The New Standard Of Counterman v. Colorado J Kovacs-Goodman, AS Sebag Harvard Journal of Law and Technology, Digest 37, 2023 | | 2023 |
| Can we get smarter than majority vote? Efficient use of individual rater’s labels for content moderation C Shin, AS Sebag 2nd Efficient Natural Language and Speech Processing Workshop, NeurIPS, 2022 | | 2022 |
| The versatility of high-content high-throughput time-lapse screening data: developing generic methods for data re-use and comparative analyses AS Sebag Ecole Nationale Supérieure des Mines de Paris, 2015 | | 2015 |
