| Learning to predict graphs with fused Gromov-Wasserstein barycenters L Brogat-Motte, R Flamary, C Brouard, J Rousu, F d’Alché-Buc International Conference on Machine Learning, 2321-2335, 2022 | 18 | 2022 |
| Duality in RKHSs with infinite dimensional outputs: Application to robust losses P Laforgue, A Lambert, L Brogat-Motte, F d’Alché-Buc International Conference on Machine Learning, 5598-5607, 2020 | 17 | 2020 |
| Vector-valued least-squares regression under output regularity assumptions L Brogat-Motte, A Rudi, C Brouard, J Rousu, F d'Alché-Buc Journal of Machine Learning Research 23 (344), 1-50, 2022 | 8 | 2022 |
| Sketch in, sketch out: Accelerating both learning and inference for structured prediction with kernels T El Ahmad, L Brogat-Motte, P Laforgue, F d’Alché-Buc International Conference on Artificial Intelligence and Statistics, 109-117, 2024 | 3 | 2024 |
| Learning output embeddings in structured prediction L Brogat-Motte, A Rudi, C Brouard, J Rousu, F d'Alché-Buc arXiv preprint arXiv:2007.14703, 2020 | 3 | 2020 |
