Publicações 2010-2021

• 2021
  • 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”, 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), Punta Cana, Dominican Republic, pp. 8029-8036, (Association for Computational Linguistics) (2021)
  • Th. Scialom, P.‑A. Dray, P. Gallinari, S. Lamprier, B. Piwowarski, J. Staiano, A. Wang : “QuestEval: Summarization Asks for Fact-based Evaluation”, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, Punta Cana (en ligne), Dominican Republic, pp. 6594-6604, (Association for Computational Linguistics) (2021)
  • M. Cesaire, L. Schott, H. Hajri, S. Lamprier, P. Gallinari : “Stochastic Sparse Adversarial Attacks”, 2021 IEEE 33^rd International Conference on Tools with Artificial Intelligence (ICTAI), Washington, United States, pp. 1247-1254, (IEEE) (2021)
  • V. Grari, O. Hajouji, S. Lamprier, M. Detyniecki : “Learning Unbiased Representations via Rényi Minimization”, Machine Learning and Knowledge Discovery in Databases. Research Track. European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part II, vol. 12976, Lecture Notes in Computer Science, Bilbao, Spain, pp. 749-764, (Springer International Publishing) (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)
  • E. Delasalles, S. Lamprier, L. Denoyer : “Deep dynamic neural networks for temporal language modeling in author communities”, Knowledge and Information Systems (KAIS), vol. 63 (3), pp. 733-757, (Springer) (2021)
  • Th. Scialom, P.‑A. Dray, J. Staiano, S. Lamprier, B. Piwowarski : “To Beam Or Not To Beam: That is a Question of Cooperation for Language GANs”, Advances in Neural Information Processing Systems, vol. 34, Virtual, United States, pp. 26585-26597, (Curran Associates, Inc.) (2021)
  • H. Hajri, M. Cesaire, Th. Combey, S. Lamprier, P. Gallinari : “Stochastic sparse adversarial attacks”, Workshop DEEL (2021), En visio, France (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, Åland Islands, pp. 18978-18989, (Curran Associates, Inc.) (2020)
  • Th. Scialom, P.‑A. Dray, S. Lamprier, B. Piwowarski, J. Staiano : “ColdGANs: Taming Language GANs with Cautious Sampling Strategies”, (2020)
  • Th. Scialom, P.‑A. Dray, S. Lamprier, B. Piwowarski, J. Staiano : “Discriminative Adversarial Search for Abstractive Summarization”, (2020)
  • Th. Scialom, P.‑A. Dray, S. Lamprier, B. Piwowarski, J. Staiano : “MLSUM: The Multilingual Summarization Corpus”, (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”, 37^th International Conference on Machine Learning, vol. 119, Proceedings of Machine Learning Research, Virtual, Åland Islands, pp. 8555-8564, (PMLR) (2020)
  • V. Grari, S. Lamprier, M. Detyniecki : “Fairness-Aware Neural Rényi Minimization for Continuous Features”, Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}, Yokohama, Japan, pp. 2262-2268, (International Joint Conferences on Artificial Intelligence Organization) (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)
  • V. Grari, B. Ruf, S. Lamprier, M. Detyniecki : “Achieving Fairness with Decision Trees: An Adversarial Approach”, Data Science and Engineering, vol. 5 (2), pp. 99-110, (Springer) (2020)
  • J.‑Y. Franceschi, E. Delasalles, M. Chen, S. Lamprier, P. Gallinari : “Stochastic Latent Residual Video Prediction”, Proceedings of the 37^th 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 - 26^th International Conference on Neural Information Processing, vol. 11955, Lecture Notes in Computer Science, Sydney, Australia, pp. 282-294 (2019)
  • E. Delasalles, S. Lamprier, L. Denoyer : “Learning Dynamic Author Representations with Temporal Language Models”, 2019 IEEE International Conference on Data Mining (ICDM), Beijing, China, pp. 120-129, (IEEE) (2019)
  • S. Lamprier, Th. Gisselbrecht, P. Gallinari : “Contextual Bandits with Hidden Contexts: a Focused Data Capture From Social Media Streams”, Data Mining and Knowledge Discovery, 33, pp. 1853-1893, (Springer) (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 9^th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), ACL Anthology, Hong Kong, China, pp. 3237-3247, (Association for Computational Linguistics) (2019)
  • S. Lamprier : “A Recurrent Neural Cascade-based Model for Continuous-Time Diffusion”, ICML 2019 - 36^th International Conference on Machine Learning, vol. 97, Proceedings of Machine Learning Research, Long Beach, CA, United States, pp. 3632-3641, (PMLR) (2019)
  • S. Lamprier : “A Variational Topological Neural Model for Cascade-based Diffusion in Networks”, (2019)
• 2018
  • E. Delasalles, S. Lamprier, L. Denoyer : “Apprentissage de l’évolution langagière dans des communautés d’auteurs”, 15^e COnférence en Recherche d'Informations et Applications - CORIA 2018, Rennes, France (2018)
  • 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)
  • S. Bourigault, S. Lamprier, P. Gallinari : “Apprentissage de représentation pour la détection de source dans les réseaux sociaux”, COnférence en Recherche d'Informations et Applications - CORIA 2017, 14^th French Information Retrieval Conference, Marseille, France, pp. 235-250 (2017)
• 2016
  • S. Bourigault, S. Lamprier, P. Gallinari : “Learning Distributed Representations of Users for Source Detection in Online Social Networks”, 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. 265-281, (Springer) (2016)
  • Th. Gisselbrecht, S. Lamprier, P. Gallinari : “Dynamic Data Capture from Social Media Streams: A Contextual Bandit Approach.”, Tenth International Conference on Web and Social Media, ICWSM 2016, Cologne, Germany, pp. 130-139 (2016)
  • S. Bourigault, S. Lamprier, P. Gallinari : “Apprentissage de Représentations Probabilistes pour la Prédiction de Diffusions d’Informations sur les Réseaux Sociaux”, COnférence en Recherche d'Information et Applications 2016 (CORIA), Toulouse, France, pp. 89-104 (2016)
  • Th. Gisselbrecht, S. Lamprier, P. Gallinari : “Bandit Contextuel pour la Capture de Données Temps Réel sur les Médias Sociaux”, Semaine du Document Numérique et de la Recherche d'Information (SDNRI 2016), Toulouse, France, pp. 57-72 (2016)
  • N. Despres, S. Lamprier, B. Piwowarski : “Apprentissage de Modèles de Langue Neuronaux pour la Recherche d’Information”, Conférence en Recherche d'Infomations et Applications, Toulouse, France, pp. 717-732 (2016)
  • S. Bourigault, S. Lamprier, P. Gallinari : “Representation Learning for Information Diffusion through Social Networks: an Embedded Cascade Model”, International Conference on Web Search and Data Mining, San Francisco, United States, pp. 573-582, (ACM) (2016)
  • 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)
  • S. Lamprier, S. Bourigault, P. Gallinari : “Influence learning for cascade diffusion models: focus on partial orders of infections”, Social Network Analysis and Mining, vol. 6 (1), pp. 93, (Springer) (2016)
• 2015
  • Th. Gisselbrecht, S. Lamprier, P. Gallinari : “Policies for Contextual Bandit Problems with Count Payoffs.”, 27^th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2015, Vietri Sul Mare, Italy, pp. 542-549, (IEEE) (2015)
  • B. Piwowarski, S. Lamprier, N. Despres : “Parameterized Neural Network Language Models for Information Retrieval”, (2015)
  • S. Lamprier, S. Bourigault, P. Gallinari : “Extracting Diffusion Channels from Real-World Social Data: a Delay-Agnostic Learning of Transmission Probabilities”, International Conference on Advances in Social Networks Analysis and Mining 2015, Paris, France (2015)
  • Th. Gisselbrecht, P. Gallinari, S. Lamprier, L. Denoyer : “WhichStreams: A Dynamic Approach for Focused Data Capture from Large Social Media”, Ninth International Conference on Web and Social Media, ICWSM 2015, Oxford, United Kingdom, pp. 130-139 (2015)
  • S. Lamprier, N. Baskiotis, T. Ziadi, L. Hillah : “The CARE Platform for the Analysis of Behavior Model Inference Techniques”, Information and Software Technology, vol. 60, pp. 32-50, (Elsevier) (2015)
  • Th. Gisselbrecht, L. Denoyer, P. Gallinari, S. Lamprier : “Apprentissage en temps réel pour la collecte d’information dans les réseaux sociaux.”, CORIA 2015 - Conférence en Recherche d'Infomations et Applications, Paris, France, pp. 7-22 (2015)
  • Th. Gisselbrecht, L. Denoyer, P. Gallinari, S. Lamprier : “Apprentissage en temps réel pour la collecte d’information dans les réseaux sociaux”, Document numérique - Revue des sciences et technologies de l'information. Série Document numérique, vol. 18 (2-3), pp. 39-58, (Hermès) (2015)
• 2014
  • S. Lamprier, T. Ziadi, N. Baskiotis, L. Hillah : “Exact and Efficient Temporal Steering of Software Behavioral Model Inference”, Proc. of 19^th IEEE International Conference on Engineering of Complex Computer Systems (ICECCS), Tianjin, China, pp. 166-175, (IEEE) (2014)
  • S. Bourigault, C. Lagnier, S. Lamprier, L. Denoyer, P. Gallinari : “Apprentissage de représentation pour la diffusion d’Information dans les réseaux sociaux”, COnférence en Recherche d'Information et Applications 2014, CORIA 2014, Nancy, France, pp. 155-170 (2014)
  • S. Bourigault, C. Lagnier, S. Lamprier, L. Denoyer, P. Gallinari : “Learning social network embeddings for predicting information diffusion”, Proceedings of the 7^th ACM international conference on Web search and data mining, New York, United States, pp. 393-402, (ACM) (2014)
  • 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)
• 2013
  • S. Lamprier, N. Baskiotis, T. Ziadi, L. Hillah : “CARE: a platform for reliable Comparison and Analysis of Reverse-Engineering techniques”, 18^th IEEE International Conference on Engineering of Complex Computer Systems -- ICECCS, Singapore, Singapore, pp. 252-255, (IEEE) (2013)
• 2010
  • S. Lamprier, T. Amghar, B. Levrat, F. Saubion : “Query-oriented clustering: a multi-objective approach.”, ACM Symposium on Applied Computing, Sierre, Switzerland, pp. 1789-1795, (ACM) (2010)
  • S. Lamprier, T. Amghar, F. Saubion, B. Levrat : “Traveling among clusters: a way to reconsider the benefits of the cluster hypothesis.”, ACM Symposium on Applied Computing, Sierre, Switzerland, pp. 1774-1780, (ACM) (2010)
  • S. Lamprier, T. Amghar, B. Levrat, F. Saubion : “Organiser les résultats d’une recherche d’information : Clustering, répartition de l’information et facilité d’accès”, Document numérique - Revue des sciences et technologies de l'information. Série Document numérique, vol. 13 (1), pp. 9-39, (Hermès) (2010)