C. Rebuffel, Th. Scialom, L. Soulier, B. Piwowarski, S. Lamprier, J. Staiano, G. Scoutheeten, P. Gallinari : “Data-QuestEval: A Reference-less Metric for Data-to-Text Semantic Evaluation”, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), Punta Cana, Dominican Republic (2021)
M. Cesaire, L. Schott, H. Hajri, S. Lamprier, P. Gallinari : “Stochastic Sparse Adversarial Attacks”, 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), Washington, United States, pp. 1247-1254, (IEEE) (2021)
J. DonĂ , J.‑Y. Franceschi, S. Lamprier, P. Gallinari : “PDE-Driven Spatiotemporal Disentanglement”, The Ninth International Conference on Learning Representations, Vienne, Austria (2021)
J. DonĂ , J.‑Y. Franceschi, S. Lamprier, P. Gallinari : “PDE-Driven Spatiotemporal Disentanglement”, The Ninth International Conference on Learning Representations, Vienne (virtual), Austria (2021)
2020
Th. Scialom, P.‑A. Dray, S. Lamprier, B. Piwowarski, J. Staiano : “ColdGANs: Taming Language GANs with Cautious Sampling Strategies”, Advances in Neural Information Processing Systems, vol. 33, NeurIPS Proceedings, Virtual, Ă…land Islands, pp. 18978-18989, (Curran Associates, Inc.) (2020)
Th. Scialom, P.‑A. Dray, S. Lamprier, B. Piwowarski, J. Staiano : “MLSUM: The Multilingual Summarization Corpus”, 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Online, France, pp. 8051-8067, (Association for Computational Linguistics) (2020)
Th. Scialom, P.‑A. Dray, S. Lamprier, B. Piwowarski, J. Staiano : “Discriminative Adversarial Search for Abstractive Summarization”, 37th International Conference on Machine Learning, vol. 119, Proceedings of Machine Learning Research, Virtual, Ă…land Islands, pp. 8555-8564, (PMLR) (2020)
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)