| Current teams : | ACASA ALMASTY ALSOC APR BD CIAN ComplexNetworks DECISION DELYS LFI MLIA MOCAH MoVe NPA PEQUAN Phare PolSys QI RO SMA SYEL |
| Former team : | Whisper |
| Publications MLIA | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | Total |
|---|---|---|---|---|---|---|---|
| Books | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Edited books | 0 | 0 | 2 | 1 | 0 | 0 | 3 |
| Journal articles | 6 | 4 | 11 | 10 | 5 | 2 | 38 |
| Book chapters | 2 | 0 | 0 | 0 | 0 | 0 | 2 |
| Conference papers | 34 | 22 | 31 | 38 | 16 | 11 | 152 |
| Habilitations | 0 | 0 | 0 | 0 | 1 | 1 | 2 |
| Theses | 3 | 7 | 4 | 9 | 9 | 3 | 35 |
- N. Aklil, B. Girard, L. Denoyer, M. Khamassi : “Sequential Action Selection and Active Sensing for Budgeted Localization in Robot Navigation”, International Journal of Semantic Computing, vol. 12 (01), pp. 109-127, (World Scientific) [Aklil 2018]
- Th. Artières, Q. Wang, M. Chen, L. Denoyer : “Adversarial learning for modeling human motion”, The Visual Computer, pp. 1-20, (Springer Verlag) [Artières 2018]
- M. CHEVALIER, N. Thome, G. Henaff, M. Cord : “Classifying low-resolution images by integrating privileged information in deep CNNs”, Pattern Recognition Letters, vol. 116, pp. 29-35, (Elsevier) [CHEVALIER 2018]
- L. DOS SANTOS, B. Piwowarski, L. Denoyer, P. Gallinari : “Representation Learning for Classification in Heterogeneous Graphs with Application to Social Networks”, ACM Transactions on Knowledge Discovery from Data (TKDD), vol. 12 (5), pp. 1-33, (ACM) [DOS SANTOS 2018]
- Th. Durand, N. Thome, M. Cord : “SyMIL: MinMax Latent SVM for Weakly Labeled Data”, IEEE Transactions on Neural Networks and Learning Systems, vol. 29 (12), pp. 6099-6112, (IEEE) [Durand 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) [Lamprier 2018]
- A. Lopez‑Rincon, A. Tonda, M. Elati, O. Schwander, B. Piwowarski, P. Gallinari : “Evolutionary optimization of convolutional neural networks for cancer miRNA biomarkers classification”, Applied Soft Computing, vol. 65, pp. 91-100, (Elsevier) [Lopez-Rincon 2018]
- T. Mordan, N. Thome, G. Henaff, M. Cord : “End-to-End Learning of Latent Deformable Part-Based Representations for Object Detection”, International Journal of Computer Vision, (Springer Verlag) [Mordan 2018a]
- T. Postadjian, A. Le Bris, H. Sahbi, C. Mallet : “Classification à très large échelle d'images satellite à très haute résolution spatiale par réseaux de neurones convolutifs”, Revue Française de Photogrammétrie et de Télédétection, vol. 217-218, pp. 73-86, (Société Française de Photogrammétrie et de Télédétection) [Postadjian 2018b]
- E. Tonnelier, N. Baskiotis, V. Guigue, P. Gallinari : “Anomaly detection in smart card logs and distant evaluation with Twitter: a robust framework”, Neurocomputing, vol. 298, pp. 109-121, (Elsevier) [Tonnelier 2018a]
- W. Zheng, A. Bellet, P. Gallinari : “A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm”, Machine Learning, (Springer Verlag) [Zheng 2018]