EN FR
EN FR
GALEN - 2017
Overall Objectives
New Results
Bilateral Contracts and Grants with Industry
Bibliography
Overall Objectives
New Results
Bilateral Contracts and Grants with Industry
Bibliography


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