Associate Professor
Team : MLIA
Localisation : Campus Pierre et Marie CurieSorbonne Université - LIP6 Boîte courrier 169 Couloir 26-00, Étage 5, Bureau 530 4 place Jussieu 75252 PARIS CEDEX 05 FRANCE Tel: +33 1 44 27 87 80, Sylvain.Lamprier (at) nulllip6.fr
3 PhD students (Supervision / Co-supervision)
CÉSAIRE Manon : génération automatique de scénarios pour la conduite autonome
BOURIGAULT Simon : Apprentissage de la dynamique de propagation d'info dans les réseaux sociaux.
2010-2021 Publications
2021
J. Donà, J.‑Y. Franceschi, S. Lamprier, P. Gallinari : “PDE-Driven Spatiotemporal Disentanglement”, The Ninth International Conference on Learning Representations, Vienne, Austria (2021)
J. Donà, J.‑Y. Franceschi, S. Lamprier, P. Gallinari : “PDE-Driven Spatiotemporal Disentanglement”, The Ninth International Conference on Learning Representations, Vienne (virtual), Austria (2021)
A. Mustar, S. Lamprier, B. Piwowarski : “Using BERT and BART for Query Suggestion”, Joint Conference of the Information Retrieval Communities in Europe, vol. 2621, CEUR Workshop Proceedings, Samatan, France, (CEUR-WS.org) (2020)
J.‑Y. Franceschi, E. Delasalles, M. Chen, S. Lamprier, P. Gallinari : “Stochastic Latent Residual Video Prediction”, Proceedings of the 37th International Conference on Machine Learning, vol. 119, Proceedings of Machine Learning Research, Vienne, Austria, pp. 3233-3246, (PMLR) (2020)
2019
E. Delasalles, S. Lamprier, L. Denoyer : “Dynamic Neural Language Models”, ICONIP 2019 - 26th International Conference on Neural Information Processing, vol. 11955, Lecture Notes in Computer Science, Sydney, Australia, pp. 282-294 (2019)
Th. Scialom, S. Lamprier, B. Piwowarski, J. Staiano : “Answers Unite! Unsupervised Metrics for Reinforced Summarization Models”, 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), ACL Anthology, Hong Kong, China, pp. 3237-3247, (Association for Computational Linguistics) (2019)
S. Lamprier, Th. Gisselbrecht, P. Gallinari : “Profile-Based Bandit with Unknown Profiles”, Journal of Machine Learning Research, vol. 19 (53), pp. 53:1-53:40, (Microtome Publishing) (2018)
2017
S. Lamprier, Th. Gisselbrecht, P. Gallinari : “Variational Thompson Sampling for Relational Recurrent Bandits”, Joint European Conference on Machine Learning and Knowledge Discovery in Databases - ECML/PKDD 2017, vol. 10535, Lecture Notes in Computer Science, Skopje, North Macedonia, pp. 405-421, (Springer) (2017)
Th. Gisselbrecht, S. Lamprier, P. Gallinari : “Linear Bandits in Unknown Environments”, ECML PKDD 2016 - European Conference on Machine Learning and Knowledge Discovery in Databases, vol. 9852, Lecture Notes in Computer Science, Riva Del Garda, Italy, pp. 282-298, (Springer) (2016)
Th. Gisselbrecht, S. Lamprier, P. Gallinari : “Policies for Contextual Bandit Problems with Count Payoffs.”, 27th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2015, Vietri Sul Mare, Italy, pp. 542-549, (IEEE) (2015)
C. Lagnier, S. Bourigault, S. Lamprier, L. Denoyer, P. Gallinari : “Learning Information Spread in Content Networks”, ICLR 2014 - International Conference on Learning Representations, CoRR, Banff, Canada, pp. abs/1312.6169 (2014)