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Bibliography

Major publications by the team in recent years
  • 1F. Bimbot, E. Deruty, G. Sargent, E. Vincent.

    System & Contrast : A Polymorphous Model of the Inner Organization of Structural Segments within Music Pieces, in: Music Perception, June 2016, vol. 33, no 5, pp. 631-661. [ DOI : 10.1525/mp.2016.33.5.631 ]

    https://hal.inria.fr/hal-01188244
  • 2N. Duong, E. Vincent, R. Gribonval.

    Under-determined reverberant audio source separation using a full-rank spatial covariance model, in: IEEE Transactions on Audio, Speech and Language Processing, July 2010, vol. 18, no 7, pp. 1830–1840. [ DOI : 10.1109/TASL.2010.2050716 ]

    https://hal.inria.fr/inria-00541865
  • 3R. Gribonval, K. Schnass.

    Dictionary Identification - Sparse Matrix-Factorisation via _1-Minimisation, in: IEEE Transactions on Information Theory, July 2010, vol. 56, no 7, pp. 3523–3539. [ DOI : 10.1109/TIT.2010.2048466 ]

    https://hal.archives-ouvertes.fr/hal-00541297
  • 4D. K. Hammond, P. Vandergheynst, R. Gribonval.

    Wavelets on graphs via spectral graph theory, in: Applied and Computational Harmonic Analysis, March 2011, vol. 30, no 2, pp. 129–150. [ DOI : 10.1016/j.acha.2010.04.005 ]

    https://hal.inria.fr/inria-00541855
  • 5S. Kitić, L. Albera, N. Bertin, R. Gribonval.

    Physics-driven inverse problems made tractable with cosparse regularization, in: IEEE Transactions on Signal Processing, January 2016, vol. 64, no 2, pp. 335-348. [ DOI : 10.1109/TSP.2015.2480045 ]

    https://hal.inria.fr/hal-01133087
  • 6S. Kitić.

    Cosparse regularization of physics-driven inverse problems, IRISA, Inria Rennes, November 2015.

    https://hal.archives-ouvertes.fr/tel-01237323
  • 7C. Louboutin, F. Bimbot.

    Modeling the multiscale structure of chord sequences using polytopic graphs, in: 18th International Society for Music Information Retrieval Conference, Suzhou, China, October 2017.

    https://hal.archives-ouvertes.fr/hal-01653455
  • 8S. Nam, M. E. Davies, M. Elad, R. Gribonval.

    The Cosparse Analysis Model and Algorithms, in: Applied and Computational Harmonic Analysis, 2013, vol. 34, no 1, pp. 30–56, Preprint available on arXiv since 24 Jun 2011. [ DOI : 10.1016/j.acha.2012.03.006 ]

    http://hal.inria.fr/inria-00602205
  • 9A. Ozerov, E. Vincent, F. Bimbot.

    A General Flexible Framework for the Handling of Prior Information in Audio Source Separation, in: IEEE Transactions on Audio, Speech and Language Processing, May 2012, vol. 20, no 4, pp. 1118 - 1133, 16.

    http://hal.inria.fr/hal-00626962
  • 10E. Vincent, N. Bertin, R. Gribonval, F. Bimbot.

    From blind to guided audio source separation, in: IEEE Signal Processing Magazine, December 2013.

    http://hal.inria.fr/hal-00922378
Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 13H. Becker, L. Albera, P. Comon, J.-C. Nunes, R. Gribonval, J. Fleureau, P. Guillotel, I. Merlet.

    SISSY: an efficient and automatic algorithm for the analysis of EEG sources based on structured sparsity, in: NeuroImage, August 2017, vol. 157, pp. 157-172. [ DOI : 10.1016/j.neuroimage.2017.05.046 ]

    http://www.hal.inserm.fr/inserm-01617155
  • 14M. Chafii, J. Palicot, R. Gribonval.

    Wavelet modulation: An alternative modulation with low energy consumption, in: Comptes Rendus Physique, 2017, vol. 18, no 2, pp. 156-167. [ DOI : 10.1016/j.crhy.2016.11.010 ]

    https://hal.archives-ouvertes.fr/hal-01445465
  • 15C. F. Dantas, M. N. da Costa, R. da Rocha Lopes.

    Learning Dictionaries as a sum of Kronecker products, in: IEEE Signal Processing Letters, May 2017, vol. 24, no 5, pp. 559 - 563. [ DOI : 10.1109/LSP.2017.2681159 ]

    https://hal.inria.fr/hal-01672349
  • 16V. Drouard, R. Horaud, A. Deleforge, S. Ba, G. Evangelidis.

    Robust Head-Pose Estimation Based on Partially-Latent Mixture of Linear Regressions, in: IEEE Transactions on Image Processing, March 2017, vol. 26, no 3, pp. 1428 - 1440, https://arxiv.org/abs/1603.09732. [ DOI : 10.1109/TIP.2017.2654165 ]

    https://hal.inria.fr/hal-01413406
  • 17L. Le Magoarou, R. Gribonval, N. Tremblay.

    Approximate fast graph Fourier transforms via multi-layer sparse approximations, in: IEEE transactions on Signal and Information Processing over Networks, June 2017, 15 p, https://arxiv.org/abs/1612.04542. [ DOI : 10.1109/TSIPN.2017.2710619 ]

    https://hal.inria.fr/hal-01416110
  • 18A. Magassouba, N. Bertin, F. Chaumette.

    Aural servo: sensor-based control from robot audition, in: IEEE Transactions on Robotics, 2018, pp. 1-14.

    https://hal.inria.fr/hal-01694366
  • 19E. Perthame, F. Forbes, A. Deleforge.

    Inverse regression approach to robust nonlinear high-to-low dimensional mapping, in: Journal of Multivariate Analysis, January 2018, vol. 163, pp. 1 - 14. [ DOI : 10.1016/j.jmva.2017.09.009 ]

    https://hal.inria.fr/hal-01652011
  • 20G. Puy, M. E. Davies, R. Gribonval.

    Recipes for stable linear embeddings from Hilbert spaces to m, in: IEEE Transactions on Information Theory, 2017, https://arxiv.org/abs/1509.06947 - Submitted in 2015. [ DOI : 10.1109/TIT.2017.2664858 ]

    https://hal.inria.fr/hal-01203614
  • 21G. Sargent, F. Bimbot, E. Vincent.

    Estimating the structural segmentation of popular music pieces under regularity constraints, in: IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2017.

    https://hal.inria.fr/hal-01403210

Invited Conferences

International Conferences with Proceedings

  • 24F. Argelaguet, M. Ducoffe, A. Lécuyer, R. Gribonval.

    Spatial and rotation invariant 3D gesture recognition based on sparse representation, in: IEEE Symposium on 3D User Interfaces, Los Angeles, United States, March 2017, pp. 158 - 167. [ DOI : 10.1109/3DUI.2017.7893333 ]

    https://hal.inria.fr/hal-01625128
  • 25E. Byrne, R. Gribonval, P. Schniter.

    Sketched Clustering via Hybrid Approximate Message Passing, in: Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, California, United States, October 2017.

    https://hal.inria.fr/hal-01650160
  • 26A. Deleforge, Y. Traonmilin.

    Phase Unmixing : Multichannel Source Separation with Magnitude Constraints, in: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, United States, March 2017, https://arxiv.org/abs/1609.09744.

    https://hal.inria.fr/hal-01372418
  • 27A. Drémeau, A. Deleforge.

    Phase Retrieval with a Multivariate Von Mises Prior: From a Bayesian Formulation to a Lifting Solution, in: ICASSP 2017 - 42nd IEEE International Conference on Acoustics, Speech and Signal Processing, New Orleans, United States, March 2017, pp. 1-5. [ DOI : 10.1109/ICASSP.2017.7953027 ]

    https://hal.archives-ouvertes.fr/hal-01653732
  • 28C. Gaultier, S. Kitić, N. Bertin, R. Gribonval.

    AUDASCITY: AUdio Denoising by Adaptive Social CosparsITY, in: 25th European Signal Processing Conference (EUSIPCO), Kos, Greece, August 2017.

    https://hal.inria.fr/hal-01540945
  • 29H. Jain, J. Zepeda, P. Pérez, R. Gribonval.

    SUBIC: A supervised, structured binary code for image search, in: The IEEE International Conference on Computer Vision (ICCV), Venise, Italy, IEEE, October 2017, https://arxiv.org/abs/1708.02932 - Accepted at ICCV 2017 (Spotlight). [ DOI : 10.1109/ICCV.2017.96 ]

    https://hal.inria.fr/hal-01683390
  • 30S. Kataria, C. Gaultier, A. Deleforge.

    Hearing in a shoe-box : binaural source position and wall absorption estimation using virtually supervised learning , in: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New-Orleans, United States, March 2017, https://arxiv.org/abs/1609.09747.

    https://hal.inria.fr/hal-01372435
  • 31L. Le Magoarou, N. Tremblay, R. Gribonval.

    Analyzing the Approximation Error of the Fast Graph Fourier Transform, in: ASILOMAR conference on Signals, Systems, and Computers, Monterey, California, United States, October 2017.

    https://hal.archives-ouvertes.fr/hal-01627434
  • 32C. Louboutin, F. Bimbot.

    Modeling the multiscale structure of chord sequences using polytopic graphs, in: 18th International Society for Music Information Retrieval Conference, Suzhou, China, October 2017.

    https://hal.archives-ouvertes.fr/hal-01653455
  • 33C. Louboutin, F. Bimbot.

    Polytopic Graph of Latent Relations: A Multiscale Structure Model for Music Segments, in: 6th International Conference on Mathematics and Computation in Music (MCM 2017), Mexico City, Mexico, O. A. Agustín-Aquino, E. Lluis-Puebla, M. Montiel (editors), Lecture Notes in Computer Science book series, Springer, June 2017, vol. 10527.

    https://hal.archives-ouvertes.fr/hal-01653445
  • 34S. Noorzadeh, P. Maurel, T. Oberlin, R. Gribonval, C. Barillot.

    Multi-modal EEG and fMRI Source Estimation Using Sparse Constraints, in: MICCAI 2017 - 20th International Conference on Medical Image Computing and Computer Assisted Intervention, Quebec, Canada, September 2017. [ DOI : 10.1007/978-3-319-66182-7_51 ]

    https://hal.inria.fr/hal-01586495

National Conferences with Proceedings

  • 35C. FRAGA DANTAS, R. Gribonval.

    Dynamic Screening with Approximate Dictionaries, in: XXVIème colloque GRETSI, Juan-les-Pins, France, September 2017.

    https://hal.inria.fr/hal-01598021

Scientific Popularization

  • 36K. Déguernel, N. Libermann, E. Vincent.

    La musique comme une langue, March 2017, Commission française pour l’enseignement des mathématiques livret "Mathématiques et langages - Panorama du thème".

    https://hal.inria.fr/hal-01485209

Other Publications

References in notes
  • 50A. Adler, V. Emiya, M. G. Jafari, M. Elad, R. Gribonval, M. D. Plumbley.

    Audio Inpainting, in: IEEE Transactions on Audio, Speech and Language Processing, March 2012, vol. 20, no 3, pp. 922 - 932. [ DOI : 10.1109/TASL.2011.2168211 ]

    http://hal.inria.fr/inria-00577079
  • 51L. Albera, S. Kitić, N. Bertin, G. Puy, R. Gribonval.

    Brain source localization using a physics-driven structured cosparse representation of EEG signals, in: 2014 IEEE International Workshop on Machine Learning for Signal Processing, Reims, France, September 2014, 6 p.

    https://hal.archives-ouvertes.fr/hal-01027609
  • 52F. Bimbot.

    Towards an Information-Theoretic Framework for Music Structure, 2016, pp. 167-168, Invited talk at Dagstuhl Seminar 16092 on Computational Music Structure Analysis (Ed. : M. Müller, E. Chew, J.P. Bello). [ DOI : 10.4230/DagRep.6.2.147 ]

    https://hal.archives-ouvertes.fr/hal-01421013
  • 53A. Bonnefoy, V. Emiya, L. Ralaivola, R. Gribonval.

    Dynamic Screening: Accelerating First-Order Algorithms for the Lasso and Group-Lasso, in: IEEE Transactions on Signal Processing, 2015, vol. 63, no 19, 20 p. [ DOI : 10.1109/TSP.2015.2447503 ]

    https://hal.archives-ouvertes.fr/hal-01084986
  • 54A. Bourrier.

    Compressed sensing and dimensionality reduction for unsupervised learning, Université Rennes 1, May 2014.

    https://tel.archives-ouvertes.fr/tel-01023030
  • 55A. Bourrier, R. Gribonval, P. Pérez.

    Compressive Gaussian Mixture Estimation, in: Signal Processing with Adaptive Sparse Structured Representations (SPARS) 2013, Switzerland, July 2013.

    http://hal.inria.fr/hal-00811819
  • 56A. Bourrier, R. Gribonval, P. Pérez.

    Compressive Gaussian Mixture Estimation, in: ICASSP - 38th International Conference on Acoustics, Speech, and Signal Processing, Vancouver, Canada, 2013, pp. 6024-6028.

    http://hal.inria.fr/hal-00799896
  • 57A. Bourrier, R. Gribonval, P. Pérez.

    Estimation de mélange de Gaussiennes sur données compressées, in: 24ème Colloque Gretsi, France, September 2013, 191 p.

    http://hal.inria.fr/hal-00839579
  • 58M. Chafii.

    Study of a new multicarrier waveform with low PAPR, CentraleSupélec, October 2016.

    https://hal.archives-ouvertes.fr/tel-01399509
  • 59M. Chafii, J. Palicot, R. Gribonval, F. Bader.

    A Necessary Condition for Waveforms with Better PAPR than OFDM, in: IEEE Transactions on Communications, 2016. [ DOI : 10.1109/TCOMM.2016.2584068 ]

    https://hal.inria.fr/hal-01128714
  • 60M. Chafii, J. Palicot, R. Gribonval.

    A PAPR upper bound of generalized waveforms for multi-carrier modulation systems, in: 6th International Symposium on Communications, Control, and Signal Processing - ISCCSP 2014, Athènes, Greece, May 2014, pp. 461 - 464. [ DOI : 10.1109/ISCCSP.2014.6877913 ]

    https://hal-supelec.archives-ouvertes.fr/hal-01072519
  • 61M. Chafii, J. Palicot, R. Gribonval.

    Closed-form Approximations of the PAPR Distribution for Multi-Carrier Modulation Systems, in: EUSIPCO 2014 - European Signal Processing Conference, Lisbonne, Portugal, September 2014.

    https://hal.inria.fr/hal-01054126
  • 62M. Chafii, J. Palicot, R. Gribonval.

    Closed-form approximations of the peak-to-average power ratio distribution for multi-carrier modulation and their applications, in: EURASIP Journal on Advances in Signal Processing, 2014, vol. 2014, no 1, 121 p. [ DOI : 10.1186/1687-6180-2014-121 ]

    https://hal.inria.fr/hal-01056153
  • 63M. Chafii, J. Palicot, R. Gribonval.

    L'optimalité de l'OFDM en termes de performance en PAPR, in: 25ème Colloque Gretsi 2015, Lyon, France, September 2015.

    https://hal-supelec.archives-ouvertes.fr/hal-01165509
  • 64M. Chafii, J. Palicot, R. Gribonval.

    Dispositif de communication à modulation temps-fréquence adaptative, July 2016, no Numéro de demande : 1656806 ; Numéro de soumission : 1000356937.

    https://hal.inria.fr/hal-01375661
  • 65A. Deleforge, F. Forbes, S. Ba, R. Horaud.

    Hyper-Spectral Image Analysis With Partially Latent Regression and Spatial Markov Dependencies, in: IEEE Journal of Selected Topics in Signal Processing, 2015, vol. 9, no 6, pp. 1037–1048.
  • 66A. Deleforge, F. Forbes, R. Horaud.

    Acoustic space learning for sound-source separation and localization on binaural manifolds, in: International journal of neural systems, 2015, vol. 25, no 01, 1440003 p.

    https://hal.archives-ouvertes.fr/hal-00960796
  • 67A. Deleforge, F. Forbes, R. Horaud.

    High-dimensional regression with gaussian mixtures and partially-latent response variables, in: Statistics and Computing, 2015, vol. 25, no 5, pp. 893–911.
  • 68A. Deleforge, R. Horaud, Y. Y. Schechner, L. Girin.

    Co-localization of audio sources in images using binaural features and locally-linear regression, in: IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 2015, vol. 23, no 4, pp. 718–731.
  • 69A. Deleforge, W. Kellermann.

    Phase-optimized K-SVD for signal extraction from underdetermined multichannel sparse mixtures, in: Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on, IEEE, 2015, pp. 355–359.
  • 70M. A. Gerzon.

    Periphony: With-Height Sound Reproduction, in: J. Audio Eng. Soc, 1973, vol. 21, no 1, pp. 2–10.

    http://www.aes.org/e-lib/browse.cfm?elib=2012
  • 71R. Giryes, S. Nam, M. Elad, R. Gribonval, M. E. Davies.

    Greedy-Like Algorithms for the Cosparse Analysis Model, in: Linear Algebra and its Applications, January 2014, vol. 441, pp. 22–60, partially funded by the ERC, PLEASE project, ERC-2011-StG-277906. [ DOI : 10.1016/j.laa.2013.03.004 ]

    http://hal.inria.fr/hal-00716593
  • 72N. Keriven, A. Bourrier, R. Gribonval, P. Pérez.

    Sketching for Large-Scale Learning of Mixture Models, in: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), Shanghai, China, March 2016.

    https://hal.inria.fr/hal-01208027
  • 73N. Keriven, R. Gribonval.

    Compressive Gaussian Mixture Estimation by Orthogonal Matching Pursuit with Replacement, July 2015, SPARS 2015.

    https://hal.inria.fr/hal-01165984
  • 74S. Kitić, N. Bertin, R. Gribonval.

    A review of cosparse signal recovery methods applied to sound source localization, in: Le XXIVe colloque Gretsi, Brest, France, September 2013.

    http://hal.inria.fr/hal-00838080
  • 75S. Kitić, N. Bertin, R. Gribonval.

    Audio Declipping by Cosparse Hard Thresholding, August 2014, iTwist - 2nd international - Traveling Workshop on Interactions between Sparse models and Technology.

    https://hal.inria.fr/hal-00922497
  • 76S. Kitić, N. Bertin, R. Gribonval.

    Hearing behind walls: localizing sources in the room next door with cosparsity, in: ICASSP - IEEE International Conference on Acoustics, Speech, and Signal Processing, Florence, Italy, May 2014. [ DOI : 10.1109/ICASSP.2014.6854168 ]

    https://hal.inria.fr/hal-00904779
  • 77S. Kitić, N. Bertin, R. Gribonval.

    Hearing behind walls: localizing sources in the room next door with cosparsity, in: ICASSP - IEEE International Conference on Acoustics, Speech, and Signal Processing, Florence, Italy, May 2014. [ DOI : 10.1109/ICASSP.2014.6854168 ]

    https://hal.inria.fr/hal-00904779
  • 78S. Kitić, N. Bertin, R. Gribonval.

    Sparsity and cosparsity for audio declipping: a flexible non-convex approach, in: LVA/ICA 2015 - The 12th International Conference on Latent Variable Analysis and Signal Separation, Liberec, Czech Republic, August 2015, 8 p.

    https://hal.inria.fr/hal-01159700
  • 79M. Kowalski, K. Siedenburg, M. Dörfler.

    Social Sparsity! Neighborhood Systems Enrich Structured Shrinkage Operators, in: IEEE Transactions on Signal Processing, May 2013, vol. 61, no 10, pp. 2498 - 2511. [ DOI : 10.1109/TSP.2013.2250967 ]

    https://hal.archives-ouvertes.fr/hal-00691774
  • 80L. Le Magoarou, R. Gribonval, A. Gramfort.

    FAμST: speeding up linear transforms for tractable inverse problems, in: European Signal Processing Conference (EUSIPCO), Nice, France, August 2015.

    https://hal.archives-ouvertes.fr/hal-01156478
  • 81L. Le Magoarou, R. Gribonval.

    Chasing butterflies: In search of efficient dictionaries, in: International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, Australia, April 2015. [ DOI : 10.1109/ICASSP.2015.7178579 ]

    https://hal.archives-ouvertes.fr/hal-01104696
  • 82L. Le Magoarou, R. Gribonval.

    Are There Approximate Fast Fourier Transforms On Graphs?, in: International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, March 2016.

    https://hal.archives-ouvertes.fr/hal-01254108
  • 83L. Le Magoarou, R. Gribonval.

    Flexible Multi-layer Sparse Approximations of Matrices and Applications, in: IEEE Journal of Selected Topics in Signal Processing, June 2016. [ DOI : 10.1109/JSTSP.2016.2543461 ]

    https://hal.inria.fr/hal-01167948
  • 84L. Le Magoarou.

    Efficient matrices for signal processing and machine learning, INSA de Rennes, November 2016.

    https://tel.archives-ouvertes.fr/tel-01412558
  • 85A. Liutkus, R. Badeau.

    Generalized Wiener filtering with fractional power spectrograms, in: Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on, IEEE, 2015, pp. 266–270.
  • 86C. Louboutin, F. Bimbot.

    Description of Chord Progressions by Minimal Transport Graphs Using the System & Contrast Model, in: ICMC 2016 - 42nd International Computer Music Conference, Utrecht, Netherlands, September 2016.

    https://hal.archives-ouvertes.fr/hal-01421023
  • 87A. Magassouba, N. Bertin, F. Chaumette.

    Audio-based robot controlfrom interchannel level difference and absolute sound energy, in: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS'16, Daejeon, South Korea, October 2016, pp. 1992-1999.

    https://hal.inria.fr/hal-01355394
  • 88A. Magassouba, N. Bertin, F. Chaumette.

    Binaural auditory interaction without HRTF for humanoid robots: A sensor-based control approach, in: Workshop on Multimodal Sensor-based Control for HRI and soft manipulation, IROS'2016, Daejeon, South Korea, October 2016.

    https://hal.inria.fr/hal-01408422
  • 89A. Magassouba, N. Bertin, F. Chaumette.

    First applications of sound-based control on a mobile robot equipped with two microphones, in: IEEE Int. Conf. on Robotics and Automation, ICRA'16, Stockholm, Sweden, May 2016.

    https://hal.inria.fr/hal-01277589
  • 90S. Nam, R. Gribonval.

    Physics-driven structured cosparse modeling for source localization, in: Acoustics, Speech and Signal Processing, IEEE International Conference on (ICASSP 2012), Kyoto, Japon, IEEE, 2012.

    http://hal.inria.fr/hal-00659405
  • 91A. A. Nugraha, A. Liutkus, E. Vincent.

    Multichannel audio source separation with deep neural networks, in: IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2016, vol. 24, no 9, pp. 1652–1664.
  • 92A. Ozerov, C. Févotte.

    Multichannel nonnegative matrix factorization in convolutive mixtures for audio source separation, in: IEEE Transactions on Audio, Speech, and Language Processing, 2010, vol. 18, no 3, pp. 550–563.
  • 93G. Puy, P. Vandergheynst, R. Gribonval, Y. Wiaux.

    Universal and efficient compressed sensing by spread spectrum and application to realistic Fourier imaging techniques, in: EURASIP Journal on Advances in Signal Processing, 2012. [ DOI : 10.1186/1687-6180-2012-6 ]

    http://hal.inria.fr/inria-00582432
  • 94Y. Salaün, E. Vincent, N. Bertin, N. Souviraà-Labastie, X. Jaureguiberry, D. Tran, F. Bimbot.

    The Flexible Audio Source Separation Toolbox Version 2.0, May 2014, ICASSP.

    https://hal.inria.fr/hal-00957412
  • 95G. Sargent.

    Music structure estimation using multi-criteria analysis and regularity constraints, Université Rennes 1, February 2013.

    https://tel.archives-ouvertes.fr/tel-00853737
  • 96A. Schmidt, A. Deleforge, W. Kellermann.

    Ego-Noise Reduction Using a Motor Data-Guided Multichannel Dictionary, in: International Conference on Intelligent Robots and Systems (IROS), 2016, Daejon, South Korea, IEEE/RSJ, October 2016, pp. 1281-1286.

    https://hal.inria.fr/hal-01415723
  • 97Y. Traonmilin, R. Gribonval.

    Stable recovery of low-dimensional cones in Hilbert spaces: One RIP to rule them all, in: Applied and Computational Harmonic Analysis, September 2016.

    https://hal.inria.fr/hal-01207987