| Équipes actuelles : | ACASA ALMASTY ALSOC APR BD CIAN ComplexNetworks DECISION DELYS LFI MOCAH MoVe NPA PEQUAN Phare PolSys QI RO SMA SYEL |
| Ancienne équipe : | MLIA |
| Publications MLIA | 2017 | 2018 | 2019 | 2020 | 2021 | Total |
|---|---|---|---|---|---|---|
| Livres | 0 | 0 | 0 | 0 | 0 | 0 |
| Éditions de livres | 0 | 2 | 2 | 0 | 0 | 4 |
| Articles de revues | 4 | 11 | 10 | 5 | 5 | 35 |
| Chapitres de livres | 0 | 0 | 0 | 0 | 0 | 0 |
| Conférences | 22 | 31 | 39 | 25 | 38 | 155 |
| Habilitations | 0 | 0 | 0 | 1 | 1 | 2 |
| Thèses | 7 | 4 | 9 | 9 | 5 | 34 |
- N. Aklil, B. Girard, M. Khamassi, L. Denoyer : “Sequential Action Selection for Budgeted Localization in Robots”, IEEE Robotic Computing 2017, Taichung, Taiwan, Province of China, pp. 97-100 [Aklil 2017]
- L. Azzopardi, J. Pickens, Ch. Shah, L. Soulier, L. Tamine : “Second International Workshop On the Evaluation of Collaborative Information Seeking and Retrieval (Ecol'17)”, Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval, Oslo, Norway [Azzopardi 2017]
- H. Ben‑younes, R. Cadene, M. Cord, N. Thome : “MUTAN: Multimodal Tucker Fusion for Visual Question Answering”, 2017 IEEE International Conference on Computer Vision (ICCV), 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy, pp. 2631-2639, (IEEE) [Ben-younes 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, 14th French Information Retrieval Conference, Marseille, France, pp. 235-250 [Bourigault 2017]
- M. Chen, L. Denoyer : “Multi-view Generative Adversarial Networks”, ECML PKDD 2017, vol. 10535, ECML PKDD 2017: Machine Learning and Knowledge Discovery in Databases, Skopje, North Macedonia, pp. 175-188 [Chen 2017]
- G. Contardo, L. Denoyer, Th. Artières : “A Meta-Learning Approach to One-Step Active-Learning”, International Workshop on Automatic Selection, Configuration and Composition of Machine Learning Algorithms, vol. 1998, CEUR Workshop Proceedings, Skopje, North Macedonia, pp. 28-40, (CEUR) [Contardo 2017]
- Ch. Dias , V. Guigue, P. Gallinari : “Passé, présent, futurs : induction de carrières professionnelles à partir de CV”, COnférence en Recherche d'Informations et Applications - CORIA 2017, 14th French Information Retrieval Conference, Marseille, France, pp. 281-296 [Dias 2017a]
- Ch. Dias , V. Guigue, P. Gallinari : “Text-based collaborative filtering for cold-start soothing and recommendation enrichment”, AISR2017, Paris, France [Dias 2017b]
- L. DOS SANTOS, B. Piwowarski, P. Gallinari : “Gaussian Embeddings for Collaborative Filtering”, Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, Tokyo, Japan, pp. 1065-1068, (ACM) [DOS SANTOS 2017]
- Th. Durand, T. Mordan, N. Thome, M. Cord : “WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation”, IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, United States, pp. 5957-5966 [Durand 2017]
- G. Lample, N. Zeghidour, N. Usunier, A. Bordes, L. Denoyer, M. Ranzato : “Fader Networks: Generating Image Variations by Sliding Attribute Values”, 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, United States, pp. 5969-5978 [Lample 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) [Lamprier 2017]
- T. Mordan, N. Thome, M. Cord, G. Henaff : “Deformable Part-based Fully Convolutional Network for Object Detection”, British Machine Vision Conference (BMVC), London, United Kingdom [Mordan 2017]
- G.‑H. Nguyen, L. Soulier, L. Tamine, N. Bricon‑Souf : “DSRIM: A Deep Neural Information Retrieval Model Enhanced by a Knowledge Resource Driven Representation of Documents”, The 3rd ACM International Conference on the Theory of Information Retrieval, Amsterdam, Netherlands [Nguyen 2017a]
- G.‑H. Nguyen, L. Soulier, L. Tamine, N. Bricon‑Souf : “Modèle Neuronal de Recherche d'Information Augmenté par une Ressource Sémantique”, Conférence francophone en Recherche d'Information et Applications (CORIA 2017), Marseille, France [Nguyen 2017b]
- G.‑H. Nguyen, L. Tamine, L. Soulier, N. Souf : “Apprentissage de représentation des documents médicaux guidé par les concepts pour la recherche d'information”, Actes du symposium SIIM 2017, Toulouse, France, pp. 1-8 [Nguyen 2017c]
- G.‑H. Nguyen, L. Tamine, L. Soulier, N. Souf : “Learning Concept-Driven Document Embeddings for Medical Information Search”, Conference on Artificial Intelligence in Medicine (AIME 2017), Vienna, Austria [Nguyen 2017d]
- T. Postadjian, A. Le Bris, H. Sahbi, C. Mallet : “Investigating the potential of deep neural networks for large-scale classification of very high resolution satellite images”, ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. IV-1/W1, Hanovre, Germany, pp. 183-190 [Postadjian 2017]
- M. Sangnier, O. Fercoq, F. D'Alché‑Buc : “Data sparse nonparametric regression with epsilon-insensitive losses”, 9th Asian Conference on Machine Learning (ACML 2017), vol. 77, Proceedings of Machine Learning Research, Séoul, Korea, Republic of, pp. 192-207 [Sangnier 2017]
- E. Tonnelier, N. Baskiotis, V. Guigue, P. Gallinari : “Anomaly detection and characterization in smart card logs using NMF and Tweets”, ESANN 2017 - 25th European Symposium on Artificial Neural Networks, Bruges, Belgium [Tonnelier 2017]
- É. Zablocki, P. Bordes, L. Soulier, B. Piwowarski, P. Gallinari : “LIP6@CLEF2017: Multi-Modal Spatial Role Labeling using Word Embeddings Working notes”, CLEF 2017 Working Notes, Dublin, Ireland [Zablocki 2017]
- A. Ziat, E. Delasalles, L. Denoyer, P. Gallinari : “Spatio-Temporal Neural Networks for Space-Time Series Forecasting and Relations Discovery”, 2017 IEEE International Conference on Data Mining (ICDM), 2017 IEEE International Conference on Data Mining (ICDM), La Nouvelle Orléans, LA, United States, pp. 705-714, (IEEE) [Ziat 2017]