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Bibliography

Publications of the year

Articles in International Peer-Reviewed Journals

  • 1F. 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, 2016.
    https://hal.archives-ouvertes.fr/hal-01418393
  • 2S. 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, 2016. [ DOI : 10.1007/s11263-016-0925-2 ]
    https://hal.archives-ouvertes.fr/hal-01359094
  • 3E. Chouzenoux, J.-C. Pesquet.
    Convergence Rate Analysis of the Majorize-Minimize Subspace Algorithm, in: IEEE Signal Processing Letters, 2016, vol. 23, no 9, pp. 1284 - 1288. [ DOI : 10.1109/LSP.2016.2593589 ]
    https://hal.archives-ouvertes.fr/hal-01373641
  • 4M. Cimpoi, S. Maji, I. Kokkinos, A. Vedaldi.
    Deep filter banks for texture recognition, description, and segmentation , in: International Journal of Computer Vision, January 2016.
    https://hal.inria.fr/hal-01263622
  • 5R. Gadde, R. Marlet, N. Paragios.
    Learning Grammars for Architecture-Specific Facade Parsing, in: International Journal of Computer Vision, 2016. [ DOI : 10.1007/s11263-016-0887-4 ]
    https://hal.inria.fr/hal-01429246
  • 6V. 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
  • 7N. Komodakis, M. P. Kumar, N. Paragios.
    Hyper-Graphs Inference through Convex Relaxations and Move Making Algorithms: Contributions and Applications in Artificial Vision, in: Foundations and Trends in Computer Graphics and Vision, May 2016, vol. 10, no 1, pp. 1-102. [ DOI : 10.1561/0600000066 ]
    https://hal.archives-ouvertes.fr/hal-01429215
  • 8N. Paragios, E. Ferrante, B. Glocker, N. Komodakis, S. Parisot, E. I. Zacharaki.
    (Hyper)-Graphical Models in Biomedical Image Analysis, in: Medical Image Analysis, 2016. [ DOI : 10.1016/j.media.2016.06.028 ]
    https://hal.archives-ouvertes.fr/hal-01359107
  • 9E. 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
  • 10E. 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
  • 11M. Vakalopoulou, K. Karantzalos, N. Komodakis, N. Paragios.
    Graph-Based Registration, Change Detection, and Classification in Very High Resolution Multitemporal Remote Sensing Data, in: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, vol. 9, pp. 2940 - 2951. [ DOI : 10.1109/JSTARS.2016.2557081 ]
    https://hal.inria.fr/hal-01413419
  • 12E. I. Zacharaki, I. Mporas, K. Garganis, V. Megalooikonomou.
    Spike pattern recognition by supervised classification in low dimensional embedding space, in: Brain Informatics, 2016. [ DOI : 10.1007/s40708-016-0044-4 ]
    https://hal.archives-ouvertes.fr/hal-01359155
  • 13Y. Zeng, C. Wang, X. Gu, D. Samaras, N. Paragios.
    Higher-Order Graph Principles towards Non-Rigid Surface Registration, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, December 2016, vol. 38, no 12, pp. 2416 - 2429. [ DOI : 10.1109/TPAMI.2016.2528240 ]
    https://hal.archives-ouvertes.fr/hal-01429216

International Conferences with Proceedings

  • 14A. Amidi, S. Amidi, D. Vlachakis, N. Paragios, E. I. Zacharaki.
    A Machine Learning Methodology for Enzyme Functional Classification Combining Structural and Protein Sequence Descriptors, in: Bioinformatics and Biomedical Engineering, Granada, Spain, April 2016, pp. 728-738. [ DOI : 10.1007/978-3-319-31744-1_63 ]
    https://hal.archives-ouvertes.fr/hal-01359157
  • 15E. Belilovsky, G. Varoquaux, M. B. Blaschko.
    Testing for Differences in Gaussian Graphical Models: Applications to Brain Connectivity, in: Neural Information Processing Systems (NIPS) 2016, Barcelona, Spain, December 2016.
    https://hal.inria.fr/hal-01248844
  • 16S. Cadoni, E. Chouzenoux, J.-C. Pesquet, C. Chaux.
    A block parallel majorize-minimize memory gradient algorithm, in: IEEE International Conference on Image Processing (ICIP 2016), Phoenix, AZ, United States, September 2016, pp. 3194 - 3198. [ DOI : 10.1109/ICIP.2016.7532949 ]
    https://hal.archives-ouvertes.fr/hal-01418417
  • 17S. Chandra, I. Kokkinos.
    Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs, in: European Conference on Computer Vision, Amsterdam, Netherlands, September 2016. [ DOI : 10.5244/C.29.187 ]
    https://hal.inria.fr/hal-01410872
  • 18A. Cherni, E. Chouzenoux, M.-A. Delsuc.
    Proximity Operators for a Class of Hybrid Sparsity+Entropy Priors. Application to DOSY NMR Signal Reconstruction, in: International Symposium on Signal, Image, Video and Communications (ISIVC 2016), Tunis, Tunisia, November 2016, vol. In Proceedings of the International Symposium on Signal, Image, Video and Communications (ISIVC 2016).
    https://hal.archives-ouvertes.fr/hal-01421741
  • 19G. Chierchia, N. Pustelnik, J.-C. Pesquet.
    Random primal-dual proximal iterations for sparse multiclass SVM, in: IEEE International Workshop on Machine Learning for Signal Processing, Vietri sul Mare, Italy, September 2016. [ DOI : 10.1109/MLSP.2016.7738833 ]
    https://hal.archives-ouvertes.fr/hal-01419697
  • 20P. L. Combettes, J.-C. Pesquet.
    Stochastic forward-backward and primal-dual approximation algorithms with application to online image restoration, in: European Signal and Image Processing Conference (EUSIPCO 2016), Budapest, Hungary, August 2016, pp. 1813 - 1817. [ DOI : 10.1109/EUSIPCO.2016.7760561 ]
    https://hal.archives-ouvertes.fr/hal-01422154
  • 21A. Guler, N. Kardaris, S. Chandra, V. Pitsikalis, C. Werner, K. Hauer, C. Tzsafestas, P. Maragos, I. Kokkinos.
    Human Joint Angle Estimation and Gesture Recognition for Assistive Robotic Vision, in: ACVR, ECCV, Amsterdam, Netherlands, G. Hua, H. Jégou (editors), LNCS - Lecture Notes in Computer Science, Springer, October 2016, vol. 9914, pp. 415 - 431. [ DOI : 10.1007/978-3-319-48881-3_29 ]
    https://hal.inria.fr/hal-01410854
  • 22S. Kinauer, M. Berman, I. Kokkinos.
    Monocular Surface Reconstruction using 3D Deformable Part Models, in: "Geometry Meets Deep Learning" in ECCV 2016, Amsterdam, Netherlands, ECCV 2016 Workshops, Part III, LNCS 9915 proceedings, October 2016, vol. 9915, pp. 296-308. [ DOI : 10.1007/978-3-319-49409-8_24 ]
    https://hal.inria.fr/hal-01416479
  • 23E. N. Kornaropoulos, E. I. Zacharaki, P. Zerbib, C. Lin, A. Rahmouni, N. Paragios.
    Deformable group-wise registration using a physiological model: application to DIffusion-Weighted MRI, in: IEEE International Conference on Image Processing (ICIP), Phoenix, Arizona, United States, Deformable group-wise registration using a physiological model: application to DIffusion-Weighted MRI, September 2016.
    https://hal.archives-ouvertes.fr/hal-01324238
  • 24E. N. Kornaropoulos, E. I. Zacharaki, P. Zerbib, C. Lin, A. Rahmouni, N. Paragios.
    Optimal estimation of diffusion in DW-MRI by high-order MRF-based joint deformable registration and diffusion modeling, in: WBIR 2016 - 7th International Workshop on Biomedical Image Registration, Las Vegas, Nevada, United States, Optimal estimation of diffusion in DW-MRI by high-order MRF-based joint deformable registration and diffusion modeling, July 2016.
    https://hal.archives-ouvertes.fr/hal-01324229
  • 25A. Osokin, J.-B. Alayrac, I. Lukasewitz, P. K. Dokania, S. Lacoste-Julien.
    Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs, in: International Conference on Machine Learning (ICML 2016), New York, United States, 2016, Appears in Proceedings of the 33rd International Conference on Machine Learning (ICML 2016). 31 pages.
    https://hal.archives-ouvertes.fr/hal-01323727
  • 26R. Porchetto, F. Stramana, E. Ferrante, N. Paragios.
    Rigid Slice-To-Volume Medical Image Registration through Markov Random Fields, in: Bayesian and Graphical Models for Biomedical Imaging Workshop, BAMBI (MICCAI 2016, Athens, Greece), Athens, Greece, October 2016.
    https://hal.inria.fr/hal-01355110
  • 27M. Shakeri, E. Ferrante, S. Tsogkas, S. Lippe, S. Kadoury, I. Kokkinos, N. Paragios.
    Prior-based Coregistration and Cosegmentation, in: MICCAI 2016, Athens, Greece, 2016, The first two authors contributed equally.
    https://hal.inria.fr/hal-01349189
  • 28M. Shakeri, S. Tsogkas, E. Ferrante, S. Lippe, S. Kadoury, N. Paragios, I. Kokkinos.
    Sub-cortical brain structure segmentation using F-CNN's, in: ISBI 2016: International Symposium on Biomedical Imaging, Prague, Czech Republic, 2016.
    https://hal.inria.fr/hal-01265500
  • 29A. Tzalavra, K. Dalakleidi, E. I. Zacharaki, N. Tsiaparas, F. Constantinidis, N. Paragios, K. S. Nikita.
    Comparison of Multi-resolution Analysis Patterns for Texture Classification of Breast Tumors Based On DCE-MRI, in: 7th Int. Workshop on Machine Learning in Medical Imaging (MICCAI workshop), Athens, Greece, October 2016, vol. 10019, pp. 296-304. [ DOI : 10.1007/978-3-319-47157-0_36 ]
    https://hal.archives-ouvertes.fr/hal-01359118
  • 30M. Vakalopoulou, C. Platias, M. Papadomanolaki, N. Paragios, K. Karantzalos.
    Simultaneous registration, segmentation and change detection from multisensor, multitemporal satellite image pairs, in: International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, July 2016. [ DOI : 10.1109/IGARSS.2016.7729469 ]
    https://hal.inria.fr/hal-01413373
  • 31J. B. Yu, M. Blaschko.
    A Convex Surrogate Operator for General Non-Modular Loss Functions, in: The 25th Belgian-Dutch Conference on Machine Learning, Kortrijk, Belgium, September 2016.
    https://hal.inria.fr/hal-01417108
  • 32J. Yu, M. Blaschko.
    A Convex Surrogate Operator for General Non-Modular Loss Functions, in: The 19th International Conference on Artificial Intelligence and Statistics, Cadiz, Spain, Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, May 2016.
    https://hal.inria.fr/hal-01299519
  • 33J. Yu, M. Blaschko.
    Efficient Learning for Discriminative Segmentation with Supermodular Losses, in: British Machine Vision Conference, York, United Kingdom, Proceedings of the British Machine Vision Conference, September 2016.
    https://hal.inria.fr/hal-01349000

Conferences without Proceedings

  • 34S. Chandra, G. Chrysos, I. Kokkinos.
    Surface Based Object Detection in RGBD Images, in: British Machine Vision Conference, Swansea, Wales, United Kingdom, September 2016. [ DOI : 10.5244/C.29.187 ]
    https://hal.inria.fr/hal-01263930

Internal Reports

Other Publications

  • 37E. Belilovsky, K. Kastner, G. Varoquaux, M. Blaschko.
    Learning to Discover Graphical Model Structures, May 2016, working paper or preprint.
    https://hal.inria.fr/hal-01306491
  • 38W. Bounliphone, M. B. Blaschko.
    A U-statistic Approach to Hypothesis Testing for Structure Discovery in Undirected Graphical Models, April 2016, working paper or preprint.
    https://hal.inria.fr/hal-01298279
References in notes
  • 39A. Cherni, E. Chouzenoux, M.-A. Delsuc.
    Proximity Operators for a Class of Hybrid Sparsity+Entropy Priors. Application to DOSY NMR Signal Reconstruction, in: International Symposium on Signal, Image, Video and Communications (ISIVC 2016), Tunisia, 2016.
  • 40M. Shakeri, S. Tsogkas, E. Ferrante, S. Lippe, S. Kadoury, N. Paragios, I. Kokkinos.
    Sub-cortical brain structure segmentation using F-CNN's, in: ISBI 2016: International Symposium on Biomedical Imaging, Prague, Czech Republic, 2016.
    https://hal.inria.fr/hal-01265500

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