Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
XML PDF e-pub
PDF e-Pub


Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

[1]
M.-C. Corbineau.
Proximal and Interior Point Optimization Strategies in Image Recovery, Université Paris-Saclay, Centrale Supélec, December 2019.
https://hal.archives-ouvertes.fr/tel-02428404
[2]
D. K. Lê-Huu.
Nonconvex Alternating Direction Optimization for Graphs: Inference and Learning, CentraleSupélec, Université Paris-Saclay, February 2019.
https://hal.archives-ouvertes.fr/tel-02093465

Articles in International Peer-Reviewed Journals

[3]
Ö. D. Akyildiz, E. Chouzenoux, V. Elvira, J. Míguez.
A probabilistic incremental proximal gradient method, in: IEEE Signal Processing Letters, July 2019, vol. 26, no 8, pp. 1257-1261, https://arxiv.org/abs/1812.01655 - 5 pages. [ DOI : 10.1109/LSP.2019.2926926 ]
https://hal.archives-ouvertes.fr/hal-01946642
[4]
A. Benfenati, E. Chouzenoux, J.-C. Pesquet.
Proximal approaches for matrix optimization problems: Application to robust precision matrix estimation, in: Signal Processing, April 2020, vol. 169. [ DOI : 10.1016/j.sigpro.2019.107417 ]
https://hal.archives-ouvertes.fr/hal-02422403
[5]
C. Bertocchi, E. Chouzenoux, M.-C. Corbineau, J.-C. Pesquet, M. Prato.
Deep Unfolding of a Proximal Interior Point Method for Image Restoration, in: Inverse Problems, 2019, https://arxiv.org/abs/1812.04276, forthcoming. [ DOI : 10.1088/1361-6420/ab460a ]
https://hal.archives-ouvertes.fr/hal-01943475
[6]
L. Briceño-Arias, G. Chierchia, E. Chouzenoux, J.-C. Pesquet.
A Random Block-Coordinate Douglas-Rachford Splitting Method with Low Computational Complexity for Binary Logistic Regression, in: Computational Optimization and Applications, April 2019, vol. 72, no 3, pp. 707-726, https://arxiv.org/abs/1712.09131. [ DOI : 10.1007/s10589-019-00060-6 ]
https://hal.archives-ouvertes.fr/hal-01672507
[7]
M. Castella, J.-C. Pesquet, A. Marmin.
Rational optimization for nonlinear reconstruction with approximate ℓ0 penalization, in: IEEE Transactions on Signal Processing, March 2019, vol. 67, no 6, pp. 1407-1417. [ DOI : 10.1109/TSP.2018.2890065 ]
https://hal.archives-ouvertes.fr/hal-01852289
[8]
G. Chassagnon, C. Martin, R. Marini, M. Vakalopoulou, A. Régent, L. Mouthon, N. Paragios, M.-P. Revel.
Use of Elastic Registration in Pulmonary MRI for the Assessment of Pulmonary Fibrosis in Patients with Systemic Sclerosis, in: Radiology, May 2019, vol. 291, no 2, pp. 487-492. [ DOI : 10.1148/radiol.2019182099 ]
https://hal.inria.fr/hal-02422529
[9]
G. Chassagnon, M. Vakalopoulou, N. Paragios, M.-P. Revel.
Artificial intelligence applications for thoracic imaging, in: European Journal of Radiology, February 2020, vol. 123, 108774 p. [ DOI : 10.1016/j.ejrad.2019.108774 ]
https://hal.inria.fr/hal-02422501
[10]
E. Chouzenoux, M.-C. Corbineau, J.-C. Pesquet.
A Proximal Interior Point Algorithm with Applications to Image Processing, in: Journal of Mathematical Imaging and Vision, 2019, forthcoming.
https://hal.archives-ouvertes.fr/hal-02120005
[11]
E. Chouzenoux, H. Gérard, J.-C. Pesquet.
General risk measures for robust machine learning, in: Foundations of Data Science, September 2019, vol. 1, no 3, pp. 249-269, https://arxiv.org/abs/1904.11707.
https://hal.archives-ouvertes.fr/hal-02109418
[12]
E. Chouzenoux, T. Tsz-Kit Lau, C. Lefort, J.-C. Pesquet.
Optimal Multivariate Gaussian Fitting with Applications to PSF Modeling in Two-Photon Microscopy Imaging, in: Journal of Mathematical Imaging and Vision, September 2019, vol. 61, no 7, pp. 1037-1050. [ DOI : 10.1007/s10851-019-00884-1 ]
https://hal.archives-ouvertes.fr/hal-01985663
[13]
P. L. Combettes, J.-C. Pesquet.
Deep Neural Network Structures Solving Variational Inequalities *, in: Set-Valued and Variational Analysis, 2019, forthcoming.
https://hal.archives-ouvertes.fr/hal-02425025
[14]
P. L. Combettes, J.-C. Pesquet.
Stochastic Quasi-Fejér Block-Coordinate Fixed Point Iterations With Random Sweeping II: Mean-Square and Linear Convergence, in: Mathematical Programming B, March 2019, vol. 174, no 1-2, pp. 433–451.
https://hal.archives-ouvertes.fr/hal-01964582
[15]
M.-C. Corbineau, D. Kouamé, E. Chouzenoux, J.-Y. Tourneret, J.-C. Pesquet.
Preconditioned P-ULA for Joint Deconvolution-Segmentation of Ultrasound Images - Extended Version, in: IEEE Signal Processing Letters, August 2019, vol. 26, no 10, pp. 1456–1460.
https://hal.archives-ouvertes.fr/hal-02073283
[16]
D. Genest, É. Puybareau, M. Léonard, J. Cousty, N. de Crozé, H. Talbot.
High throughput automated detection of axial malformations in Medaka fish embryo, in: Computers in Biology and Medicine, February 2019, vol. 105, pp. 157-168. [ DOI : 10.1016/j.compbiomed.2018.12.016 ]
https://hal.archives-ouvertes.fr/hal-01959606
[17]
E. Grossiord, B. Naegel, H. Talbot, L. Najman, N. Passat.
Shape-based analysis on component-graphs for multivalued image processing, in: Mathematical Morphology - Theory and Applications, 2019, vol. 3, no 1, pp. 45-70. [ DOI : 10.1515/mathm-2019-0003 ]
https://hal.univ-reims.fr/hal-01695384
[18]
E. Grossiord, N. Passat, H. Talbot, B. Naegel, S. Kanoun, I. Tal, P. Tervé, S. Ken, O. Casasnovas, M. Meignan, L. Najman.
Shaping for PET image analysis, in: Pattern Recognition Letters, 2020, forthcoming.
https://hal.archives-ouvertes.fr/hal-02155801
[19]
C. Jaquet, L. Najman, H. Talbot, L. Grady, M. Schaap, B. Spain, H. J. Kim, I. Vignon-Clementel, C. A. Taylor.
Generation of patient-specific cardiac vascular networks: a hybrid image-based and synthetic geometric model, in: IEEE Transactions on Biomedical Engineering, April 2019, vol. 66, no 4, pp. 946-955. [ DOI : 10.1109/TBME.2018.2865667 ]
https://hal.archives-ouvertes.fr/hal-01869264
[20]
F. Malliaros, C. Giatsidis, A. N. Papadopoulos, M. Vazirgiannis.
The Core Decomposition of Networks: Theory, Algorithms and Applications, in: The VLDB Journal, 2019.
https://hal-centralesupelec.archives-ouvertes.fr/hal-01986309
[21]
A. Mekki, L. Dercle, P. Lichtenstein, G. Nasser, A. Marabelle, S. Champiat, E. Chouzenoux, C. Balleyguier, S. Ammari.
Machine learning defined diagnostic criteria for differentiating pituitary metastasis from autoimmune hypophysitis in patients undergoing immune checkpoint blockade therapy, in: European Journal of Cancer, September 2019, vol. 119, pp. 44-56. [ DOI : 10.1016/j.ejca.2019.06.020 ]
https://hal.archives-ouvertes.fr/hal-02269518
[22]
O. Merveille, B. Naegel, H. Talbot, N. Passat.
nD variational restoration of curvilinear structures with prior-based directional regularization, in: IEEE Transactions on Image Processing, 2019, vol. 28, no 8, pp. 3848-3859. [ DOI : 10.1109/TIP.2019.2901706 ]
https://hal.archives-ouvertes.fr/hal-01832636
[23]
A. Mongia, N. Jhamb, E. Chouzenoux, A. Majumdar.
Deep latent factor model for collaborative filtering, in: Signal Processing, 2020, vol. 169, 107366 p. [ DOI : 10.1016/j.sigpro.2019.107366 ]
https://hal.archives-ouvertes.fr/hal-02373934
[24]
M. Papadomanolaki, M. Vakalopoulou, K. Karantzalos.
A Novel Object-Based Deep Learning Framework for Semantic Segmentation of Very High-Resolution Remote Sensing Data: Comparison with Convolutional and Fully Convolutional Networks, in: Remote Sensing, March 2019, vol. 11, no 6, 684 p. [ DOI : 10.3390/rs11060684 ]
https://hal.inria.fr/hal-02078539
[25]
J. Robic, B. Perret, A. Nkengne, M. Couprie, H. Talbot.
Three-dimensional conditional random field for the dermal–epidermal junction segmentation, in: Journal of Medical Imaging, April 2019, vol. 6, no 02, 1 p. [ DOI : 10.1117/1.JMI.6.2.024003 ]
https://hal.archives-ouvertes.fr/hal-02155490
[26]
M. Vakalopoulou, G. Chassagnon, N. Paragios, M.-P. Revel.
Deep learning: definition and perspectives for thoracic imaging, in: European Radiology, December 2019. [ DOI : 10.1007/s00330-019-06564-3 ]
https://hal.inria.fr/hal-02422513

Invited Conferences

[27]
E. Chouzenoux, V. Elvira.
Adaptive importance sampling with scaled Langevin proposal adaptatioń, in: 17th International Conference on Computer Aided Systems Theory (EUROCAST 2019), Las Palmas de Gran Canaria, Spain, February 2019.
https://hal.archives-ouvertes.fr/hal-02314409
[28]
A. Marmin, M. Castella, J.-C. Pesquet.
Detecting the rank of a symmetric tensor, in: EUSIPCO 2019 : 27th European Signal Processing Conference, La Corogne, Spain, 2019 27th European Signal Processing Conference (EUSIPCO), IEEE, 2019, pp. 1-5. [ DOI : 10.23919/EUSIPCO.2019.8902781 ]
https://hal.archives-ouvertes.fr/hal-02284991
[29]
Y. Marnissi, E. Chouzenoux, A. Benazza-Benyahia, J.-C. Pesquet.
MM Adapted MH Methods, in: BASP 2019 - International Biomedical and Astronomical Signal Processing Frontiers workshop, Villars sur Ollon, Switzerland, February 2019.
https://hal.archives-ouvertes.fr/hal-02314412
[30]
M. Terris, E. Chouzenoux.
Stochastic MM Subspace Algorithms, in: BASP 2019 - International Biomedical and Astronomical Signal Processing Frontiers workshop, Villars sur Ollon, Switzerland, February 2019.
https://hal.archives-ouvertes.fr/hal-02314411

International Conferences with Proceedings

[31]
D. Antunes, J.-O. Lachaud, H. Talbot.
Digital Curvature Evolution Model for Image Segmentation, in: International Conference on Discrete Geometry for Computer Imagery, Noisy-le-Grand, France, Lecture Notes in Computer Science, Springer, February 2019, vol. 11414, pp. 15-26. [ DOI : 10.1007/978-3-030-14085-4_2 ]
https://hal.archives-ouvertes.fr/hal-02426946
[32]
E. Battistella, M. Vakalopoulou, T. Estienne, M. Lerousseau, R. Sun, C. Robert, N. Paragios, E. Deutsch.
Gene Expression High-Dimensional Clustering towards a Novel, Robust, Clinically Relevant and Highly Compact Cancer Signature, in: IWBBIO 2019 - 7th International Work-Conference on Bioinformatics and Biomedical Engineering, Granada, Spain, 2019.
https://hal.archives-ouvertes.fr/hal-02076104
[33]
E. Belilovsky, M. Eickenberg, E. Oyallon.
Greedy Layerwise Learning Can Scale to ImageNet, in: ICML 2019 - 36th International Conference on Machine Learning, Long Beach, CA, United States, June 2019, https://arxiv.org/abs/1812.11446.
https://hal.inria.fr/hal-02119398
[34]
A. Benamira, B. Devillers, E. Lesot, A. K. Ray, M. Saadi, F. Malliaros.
Semi-Supervised Learning and Graph Neural Networks for Fake News Detection, in: ASONAM 2019 - IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Vancouver, Canada, August 2019.
https://hal.archives-ouvertes.fr/hal-02334445
[35]
A. Cherni, E. Chouzenoux, L. Duval, J.-C. Pesquet.
A Novel Smoothed Norm Ratio for Sparse Signal Restoration Application to Mass Spectrometry, in: SPARS ( Signal Processing with Adaptive Sparse Structured Representations ), Toulouse, France, July 2019.
https://hal.archives-ouvertes.fr/hal-02179379
[36]
M.-C. Corbineau, C. Bertocchi, E. Chouzenoux, M. Prato, J.-C. Pesquet.
Learned Image Deblurring by Unfolding a Proximal Interior Point Algorithm, in: ICIP 2019 - 26th IEEE International Conference on Image Processing, Taipei, Taiwan, IEEE, September 2019. [ DOI : 10.1109/ICIP.2019.8803438 ]
https://hal.archives-ouvertes.fr/hal-02303511
[37]
L. El Gueddari, P. Ciuciu, E. Chouzenoux, A. Vignaud, J.-C. Pesquet.
Calibrationless oscar-based image reconstruction in compressed sensing parallel MRI, in: ISBI 2019 - IEEE International Symposium on Biomedical Imaging, Venise, Italy, April 2019.
https://hal.inria.fr/hal-02101262
[38]
V. Elvira, E. Chouzenoux.
Langevin-based Strategy for Efficient Proposal Adaptation in Population Monte Carlo, in: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019), Brighton, United Kingdom, May 2019. [ DOI : 10.1109/ICASSP.2019.8682284 ]
https://hal.archives-ouvertes.fr/hal-02431677
[39]
D. Genest, M. Léonard, J. Cousty, N. de Crozé, H. Talbot.
Atlas-based automated detection of swim bladder in Medaka embryo, in: International Symposium on Mathematical Morphology (ISMM), Saarbrücken, Germany, Lecture Notes in Computer Science, Springer, May 2019, vol. 11564, pp. 496-507, https://arxiv.org/abs/1902.06130. [ DOI : 10.1007/978-3-030-20867-7_38 ]
https://hal.archives-ouvertes.fr/hal-02019658
[40]
L. E. Gueddari, E. Chouzenoux, A. Vignaud, J.-C. Pesquet, P. Ciuciu.
Online MR image reconstruction for compressed sensing acquisition in T2* imaging, in: SPIE Conference - Wavelets and Sparsity XVIII, San Diego, United States, August 2019.
https://hal.inria.fr/hal-02265538
[41]
Y. Huang, E. Chouzenoux, V. Elvira.
Particle Filtering for Online Space-Varying Blur Identification, in: IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Le Gosier, France, Proceedings of the IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, December 2019.
https://hal.archives-ouvertes.fr/hal-02406970
[42]
A. Marmin, M. Castella, J.-C. Pesquet.
Sparse signal reconstruction with a sign oracle, in: SPARS 2019 - Signal Processing with Adaptive Sparse Structured Representations - Workshop, Toulouse, France, July 2019.
https://hal.archives-ouvertes.fr/hal-02196881
[43]
Y. Marnissi, D. Abboud, E. Chouzenoux, J.-C. Pesquet, M. El-Badaoui, A. Benazza-Benyahia.
A Data Augmentation Approach for Sampling Gaussian Models in High Dimension, in: EUSIPCO 2019 - 27th European Signal Processing Conference, La Corogne, Spain, Proceedings of the 27th European Signal Processing Conference (EUSIPCO 2019), September 2019.
https://hal.archives-ouvertes.fr/hal-02314418
[44]
A. Mongia, V. Jain, E. Chouzenoux, A. Majumdar.
Deep Latent Factor Model for Predicting Drug Target Interactions, in: IEEE International Conference on Acoustics, Speech and Signal Processing, Brighton, United Kingdom, May 2019.
https://hal.archives-ouvertes.fr/hal-02406989
[45]
M. Papadomanolaki, K. Karantzalos, M. Vakalopoulou.
A multi-task deep learning framework coupling semantic segmentation and image reconstruction for very high resolution imagery, in: IGARSS 2019 - IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, July 2019.
https://hal.inria.fr/hal-02266085
[46]
M. Papadomanolaki, S. Verma, M. Vakalopoulou, S. Gupta, K. Karantzalos.
Detecting urban changes with recurrent neural networks from multitemporal Sentinel-2 data, in: IGARSS 2019 - IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, July 2019.
https://hal.inria.fr/hal-02266094
[47]
É. Puybareau, E. Carlinet, A. Benfenati, H. Talbot.
Spherical Fluorescent Particle Segmentation and Tracking in 3D Confocal Microscopy, in: International Symposium on Mathematical Morphology, ISMM 2019, Saarbrücken, Germany, Lecture Notes in Computer Science, Springer, May 2019, vol. 11564, pp. 520-531. [ DOI : 10.1007/978-3-030-20867-7_40 ]
https://hal.archives-ouvertes.fr/hal-02426948
[48]
J. Robic, B. Perret, A. Nkengne, M. Couprie, H. Talbot.
Self-dual pattern spectra for characterising the dermal-epidermal junction in 3D reflectance confocal microscopy imaging, in: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing, Saarbrücken, Germany, Lecture Notes in Computer Science, Springer, May 2019, vol. 11564, pp. 508-519. [ DOI : 10.1007/978-3-030-20867-7_39 ]
https://hal.archives-ouvertes.fr/hal-02169702
[49]
M. Sahasrabudhe, Z. Shu, E. Bartrum, R. A. Güler, D. Samaras, I. Kokkinos.
Lifting AutoEncoders: Unsupervised Learning of a Fully-Disentangled 3D Morphable Model Using Deep Non-Rigid Structure From Motion, in: The IEEE International Conference on Computer Vision (ICCV) Workshops, Seoul, South Korea, The IEEE International Conference on Computer Vision (ICCV) Workshops, November 2019.
https://hal.archives-ouvertes.fr/hal-02422596
[50]
M. Sghaier, E. Chouzenoux, G. Palma, J.-C. Pesquet, S. Muller.
A New Approach for Microcalcification Enhancement in Digital Breast Tomosynthesis Reconstruction, in: ISBI 2019 - IEEE International Symposium on Biomedical Imaging, Venise, Italy, Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI 2019), April 2019. [ DOI : 10.1109/ISBI.2019.8759534 ]
https://hal.archives-ouvertes.fr/hal-02314420
[51]
A. J.-P. Tixier, M. E. G. Rossi, F. Malliaros, J. Read, M. Vazirgiannis.
Perturb and Combine to Identify Influential Spreaders in Real-World Networks, in: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Vancouver, Canada, August 2019.
https://hal-centralesupelec.archives-ouvertes.fr/hal-01958973
[52]
M. Vakalopoulou, S. Christodoulidis, M. Sahasrabudhe, S. Mougiakakou, N. Paragios.
Image Registration of Satellite Imagery with Deep Convolutional Neural Networks, in: IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, France, IEEE, July 2019, pp. 4939-4942. [ DOI : 10.1109/IGARSS.2019.8898220 ]
https://hal.inria.fr/hal-02422555
[53]
A. Çelikkanat, F. Malliaros.
Kernel Node Embeddings, in: IEEE Global Conference on Signal and Information Processing (GlobalSIP), Ottawa, Canada, November 2019.
https://hal.archives-ouvertes.fr/hal-02423629
[54]
A. Çelikkanat, F. Malliaros.
Learning Node Embeddings with Exponential Family Distributions, in: NeurIPS 2019 - 33th Annual Conference on Neural Information Processing Systems - Workshop on Graph Representation Learning, Vancouver, Canada, December 2019.
https://hal.archives-ouvertes.fr/hal-02336000

Conferences without Proceedings

[55]
A. Cherni, E. Chouzenoux, L. Duval, J.-C. Pesquet.
Forme lissée de rapports de normes lp/lq (SPOQ) pour la reconstruction des signaux avec pénalisation parcimonieuse, in: GRETSI 2019, Lille, France, August 2019.
https://hal.archives-ouvertes.fr/hal-02179373
[56]
L. El Gueddari, P. Ciuciu, E. Chouzenoux, A. Vignaud, J.-C. Pesquet.
Online compressed sensing MR image reconstruction for high resolution T2* imaging, in: ISMRM 27th Annual Meeting and Exhibition, Montréal, Canada, May 2019.
https://hal.archives-ouvertes.fr/hal-02314904
[57]
L. El Gueddari, P. Ciuciu, E. Chouzenoux, A. Vignaud, J.-C. Pesquet.
OSCAR-based reconstruction for compressed sensing and parallel MR imaging, in: ISMRM 27th Annual Meeting and Exhibition, Montréal, Canada, May 2019.
https://hal.archives-ouvertes.fr/hal-02314911
[58]
T. Estienne, M. Vakalopoulou, S. Christodoulidis, E. Battistella, M. Lerousseau, A. Carre, G. Klausner, R. Sun, C. Robert, S. Mougiakakou, N. Paragios, E. Deutsch.
U-ReSNet: Ultimate Coupling of Registration and Segmentation with Deep Nets, in: MICCAI 2019: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019, Shenzhen, China, MICCAI, October 2019, pp. 310-319. [ DOI : 10.1007/978-3-030-32248-9_35 ]
https://hal.archives-ouvertes.fr/hal-02365899
[59]
C. Lefort, E. Chouzenoux, J.-C. Pesquet.
PLUMEE 2019 : Reconstruction numérique d'image en microscopie multiphotonique, in: 6ème Colloque francophone PLUridisciplinaire sur les Matériaux, l'Environnement et l'Electronique (PLUMEE 2019), Limoges, France, April 2019.
https://hal.archives-ouvertes.fr/hal-02426765
[60]
S. Verma, R. Verma, P. B. Sujit.
MAPEL: Multi-Agent Pursuer-Evader Learning using Situation Report, in: 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, France, IEEE, July 2019, pp. 1-8. [ DOI : 10.1109/IJCNN.2019.8852457 ]
https://hal.archives-ouvertes.fr/hal-02426661

Other Publications

[61]
A. Benfenati, F. Bonacci, T. Bourouina, H. Talbot.
Efficient position estimation of 3D fluorescent spherical beads in confocal microscopy via Poisson denoising, October 2019, working paper or preprint.
https://hal.archives-ouvertes.fr/hal-02150316
[62]
L. El Gueddari, E. Chouzenoux, A. Vignaud, P. Ciuciu.
Calibration-less parallel imaging compressed sensing reconstruction based on OSCAR regularization, September 2019, working paper or preprint.
https://hal.inria.fr/hal-02292372
[63]
B. Kas, H. Talbot, R. Ferrara, C. Richard, B. Besse, L. Mezquita, N. Lassau, C. Caramella.
Hyperprogressive disease during immunotherapy: an attempt to clarify different definitions, November 2019, working paper or preprint.
https://hal.archives-ouvertes.fr/hal-02429762