Personnel
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
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Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

  • 1E. Chouzenoux.
    Algorithmes de majoration-minimisation. Application aux problèmes inverses de grande taille en signal/image, Université Paris Est - Marne-la-Vallée, December 2017, Habilitation à diriger des recherches.
    https://hal.archives-ouvertes.fr/tel-01661236
  • 2E. N. Kornaropoulos.
    Deformable Group-wise Image Registration for Motion Estimation in 4D Medical Imaging , Ecole Centrale Paris, June 2017.
    https://hal.inria.fr/tel-01577683
  • 3E. I. Zacharaki.
    Computational methods towards image-based biomarkers and beyond, Université Paris-Est, March 2017, Habilitation à diriger des recherches.
    https://hal.inria.fr/tel-01648583

Articles in International Peer-Reviewed Journals

  • 4F. Abboud, E. Chouzenoux, J.-C. Pesquet, J.-H. Chenot, L. Laborelli.
    Dual Block Coordinate Forward-Backward Algorithm with Application to Deconvolution and Deinterlacing of Video Sequences, in: Journal of Mathematical Imaging and Vision, November 2017, vol. 59, no 3, pp. 415-431. [ DOI : 10.1007/s10851-016-0696-y ]
    https://hal.archives-ouvertes.fr/hal-01418393
  • 5S. Alchatzidis, A. Sotiras, E. I. Zacharaki, N. Paragios.
    A Discrete MRF Framework for Integrated Multi-Atlas Registration and Segmentation, in: International Journal of Computer Vision, January 2017. [ DOI : 10.1007/s11263-016-0925-2 ]
    https://hal.archives-ouvertes.fr/hal-01359094
  • 6S. Amidi, A. Amidi, D. Vlachakis, N. Paragios, E. I. Zacharaki.
    Automatic single- and multi-label enzymatic function prediction by machine learning, in: PeerJ, 2017, vol. 5, pp. 1-16. [ DOI : 10.7717/peerj.3095 ]
    https://hal.inria.fr/hal-01648529
  • 7A. Cherni, E. Chouzenoux, M.-A. Delsuc.
    PALMA, an improved algorithm for DOSY signal processing, in: Analyst, 2017, vol. 142, no 5, pp. 772 - 779. [ DOI : 10.1039/C6AN01902A ]
    https://hal.archives-ouvertes.fr/hal-01613209
  • 8E. Chouzenoux, J.-C. Pesquet.
    A Stochastic Majorize-Minimize Subspace Algorithm for Online Penalized Least Squares Estimation, in: IEEE Transactions on Signal Processing, September 2017, vol. 65, no 18, pp. 4770 - 4783. [ DOI : 10.1109/TSP.2017.2709265 ]
    https://hal.archives-ouvertes.fr/hal-01613204
  • 9E. Ferrante, N. Paragios.
    Graph-Based Slice-to-Volume Deformable Registration, in: International Journal of Computer Vision, 2017. [ DOI : 10.1007/s11263-017-1040-8 ]
    https://hal.inria.fr/hal-01576314
  • 10E. Ferrante, N. Paragios.
    Slice-to-volume medical image registration: A survey, in: Medical Image Analysis, July 2017, vol. 39, pp. 101 - 123. [ DOI : 10.1016/j.media.2017.04.010 ]
    https://hal.inria.fr/hal-01650929
  • 11V. G. Kanas, E. I. Zacharaki, G. A. Thomas, P. O. Zinn, V. Megalooikonomou, R. R. Colen.
    Learning MRI-based classification models for MGMT methylation status prediction in glioblastoma, in: Computer Methods and Programs in Biomedicine, January 2017. [ DOI : 10.1016/j.cmpb.2016.12.018 ]
    https://hal.inria.fr/hal-01423323
  • 12E. J. Limkin, R. Sun, L. Dercle, E. I. Zacharaki, C. Robert, S. Reuzé, A. Schernberg, N. Paragios, E. Deutsch, C. Ferté.
    Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology, in: Annals of Oncology, June 2017, vol. 28, no 6, pp. 1191 - 1206. [ DOI : 10.1093/annonc/mdx034 ]
    https://hal.inria.fr/hal-01648559
  • 13Y. Marnissi, Y. Zheng, E. Chouzenoux, J.-C. Pesquet.
    A Variational Bayesian Approach for Image Restoration. Application to Image Deblurring with Poisson-Gaussian Noise, in: IEEE Transactions on Computational Imaging, 2017, 16 p, forthcoming. [ DOI : 10.1109/TCI.2017.2700203 ]
    https://hal.archives-ouvertes.fr/hal-01613200
  • 14E. Pippa, V. G. Kanas, E. I. Zacharaki, V. Tsirka, M. Koutroumanidis, V. Megalooikonomou.
    EEG-based Classification of Epileptic and Non-epileptic Events using Multi-array Decomposition, in: International Journal of Monitoring and Surveillance Technologies Research, January 2017.
    https://hal.archives-ouvertes.fr/hal-01359125
  • 15E. Pippa, E. I. Zacharaki, M. Koutroumanidis, V. Megalooikonomou.
    Data fusion for paroxysmal events' classification from EEG, in: Journal of Neuroscience Methods, January 2017, vol. 275, pp. 55-65. [ DOI : 10.1016/j.jneumeth.2016.10.004 ]
    https://hal.inria.fr/hal-01426373
  • 16A. Pirayre, C. Couprie, L. Duval, J.-C. Pesquet.
    BRANE Clust: Cluster-Assisted Gene Regulatory Network Inference Refinement, in: IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017, forthcoming.
    https://hal-ifp.archives-ouvertes.fr/hal-01330638
  • 17R. Sun, E. J. Limkin, L. Dercle, S. Reuzé, E. I. Zacharaki, C. Chargari, A. Schernberg, A.-S. Dirand, A. Alexis, N. Paragios, E. Deutsch, C. Ferté, C. Robert.
    Computational medical imaging (radiomics) and potential for immuno-oncology, in: Cancer Radiothérapie, August 2017, vol. 21, no 6-7, pp. 648-654. [ DOI : 10.1016/j.canrad.2017.07.035 ]
    https://hal.inria.fr/hal-01668902
  • 18E. I. Zacharaki.
    Prediction of protein function using a deep convolutional neural network ensemble, in: PeerJ Computer Science, 2017, vol. 3, pp. 1-17. [ DOI : 10.7717/peerj-cs.124 ]
    https://hal.inria.fr/hal-01648534

International Conferences with Proceedings

  • 19E. B. Belilovsky, K. Kastner, G. Varoquaux, M. B. Blaschko.
    Learning to Discover Sparse Graphical Models, in: International Conference on Machine Learning, Sydney, Australia, August 2017, https://arxiv.org/abs/1605.06359.
    https://hal.inria.fr/hal-01306491
  • 20G. Chierchia, A. Cherni, E. Chouzenoux, J.-C. Pesquet.
    Approche de Douglas-Rachford aléatoire par blocs appliquée à la régression logistique parcimonieuse, in: GRETSI 2017, Juan les Pins, France, Actes du 26e colloque GRETSI, September 2017, pp. 1-4.
    https://hal.archives-ouvertes.fr/hal-01634525
  • 21E. Ferrante, P. K. Dokania, R. Marini, N. Paragios.
    Deformable Registration through Learning of Context-Specific Metric Aggregation, in: Machine Learning in Medical Imaging Worlshop. MLMI (MICCAI 2017), Quebec City, Canada, September 2017, https://arxiv.org/abs/1707.06263 - Accepted for publication in the 8th International Workshop on Machine Learning in Medical Imaging (MLMI 2017), in conjunction with MICCAI 2017.
    https://hal.inria.fr/hal-01650956
  • 22R. A. Guler, G. Trigeorgis, E. Antonakos, P. Snape, S. Zafeiriou, I. Kokkinos.
    DenseReg: Fully Convolutional Dense Shape Regression In-the-Wild, in: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, United States, IEEE, CVF, July 2017, pp. 6799-6808, https://arxiv.org/abs/1612.01202.
    https://hal.archives-ouvertes.fr/hal-01637896
  • 23H. Kannan, N. Komodakis, N. Paragios.
    Newton-type Methods for Inference in Higher-Order Markov Random Fields, in: IEEE International Conference on Computer Vision and Pattern Recognition, Honolulu, United States, July 2017, pp. 7224 - 7233.
    https://hal.archives-ouvertes.fr/hal-01580862
  • 24D. K. Lê-Huu, N. Paragios.
    Alternating Direction Graph Matching, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, United States, July 2017, https://arxiv.org/abs/1611.07583.
    https://hal.inria.fr/hal-01580824
  • 25E. Oyallon, E. Belilovsky, S. Zagoruyko.
    Scaling the Scattering Transform: Deep Hybrid Networks, in: International Conference on Computer Vision (ICCV), Venice, Italy, October 2017, https://arxiv.org/abs/1703.08961.
    https://hal.inria.fr/hal-01495734

Conferences without Proceedings

  • 26A. Benfenati, E. Chouzenoux, J.-C. Pesquet.
    A Proximal Approach for Solving Matrix Optimization Problems Involving a Bregman Divergence, in: BASP 2017 - International Biomedical and Astronomical Signal Processing Frontiers workshop, villars-sur-oulon, Switzerland, January 2017.
    https://hal.archives-ouvertes.fr/hal-01613292
  • 27S. Cadoni, E. Chouzenoux, J.-C. Pesquet, C. Chaux.
    A Block Parallel Majorize-Minimize Memory Gradient Algorithm, in: BASP 2017 - International Biomedical and Astronomical Signal Processing Frontiers workshop, Villars-sur-Oulon, Switzerland, January 2017, 1 p.
    https://hal.archives-ouvertes.fr/hal-01634531
  • 28V. Dudar, G. Chierchia, E. Chouzenoux, J.-C. Pesquet, V. V. Semenov.
    A Two-Stage Subspace Trust Region Approach for Deep Neural Network Training, in: 25th European Signal Processing Conference (EUSIPCO 2017), Kos Island, Greece, August 2017.
    https://hal.archives-ouvertes.fr/hal-01634538
  • 29Q. Wei, E. Chouzenoux, J.-Y. Tourneret, J.-C. Pesquet.
    A Fast Algorithm Based on a Sylvester-like Equation for LS Regression with GMRF Prior, in: CAMSAP 2017- IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Curaçao, Netherlands Antilles, December 2017.
    https://hal.archives-ouvertes.fr/hal-01635601

Scientific Popularization

  • 30S. Chandra, N. Usunier, I. Kokkinos.
    Dense and Low-Rank Gaussian CRFs Using Deep Embeddings, in: ICCV 2017 - International Conference on Computer Vision, Venice, Italy, September 2017.
    https://hal.inria.fr/hal-01646293

Other Publications

  • 31F. Abboud, E. Chouzenoux, J.-C. Pesquet, J.-H. Chenot, L. Laborelli.
    An Alternating Proximal Approach for Blind Video Deconvolution, December 2017, working paper or preprint.
    https://hal.archives-ouvertes.fr/hal-01668437
  • 32A. Benfenati †, E. Chouzenoux, J.-C. Pesquet.
    A proximal approach for a class of matrix optimization problems, December 2017, working paper or preprint.
    https://hal.archives-ouvertes.fr/hal-01673027
  • 33L. 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, December 2017, working paper or preprint.
    https://hal.archives-ouvertes.fr/hal-01672507
  • 34Y. Marnissi, E. Chouzenoux, A. Benazza-Benyahia, J.-C. Pesquet.
    An Auxiliary Variable Method for MCMC Algorithms in High Dimension, December 2017, working paper or preprint.
    https://hal.archives-ouvertes.fr/hal-01661234
  • 35J. Yu, M. Blaschko.
    The Lovász Hinge: A Novel Convex Surrogate for Submodular Losses, May 2017, working paper or preprint.
    https://hal.inria.fr/hal-01241626
  • 36Y. Zheng, A. Pirayre, L. Duval, J.-C. Pesquet.
    Joint restoration/segmentation of multicomponent images with variationalBayes and higher-order graphical models (HOGMep), May 2017, working paper or preprint.
    https://hal-ifp.archives-ouvertes.fr/hal-01528856