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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, 2016, 41 p, To appear - http://mp.ucpress.edu/.

    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
  • 7S. 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
  • 8A. 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
  • 9G. Sargent.

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

    https://tel.archives-ouvertes.fr/tel-00853737
  • 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

  • 12H. Becker, L. Albera, P. Comon, R. Gribonval, F. Wendling, I. Merlet.

    Localization of Distributed EEG Sources in the Context of Epilepsy: A Simulation Study, in: IRBM, 2016. [ DOI : 10.1016/j.irbm.2016.04.001 ]

    https://hal.archives-ouvertes.fr/hal-01359237
  • 13F. 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, 2016, 41 p.

    https://hal.inria.fr/hal-01188244
  • 14M. 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
  • 15S. 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
  • 16L. 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
  • 17G. Puy, N. Tremblay, R. Gribonval, P. Vandergheynst.

    Random sampling of bandlimited signals on graphs, in: Applied and Computational Harmonic Analysis, June 2016. [ DOI : 10.1016/j.acha.2016.05.005 ]

    https://hal.inria.fr/hal-01229578
  • 18G. 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
  • 19N. Shahid, N. Perraudin, V. Kalofolias, G. Puy, P. Vandergheynst.

    Fast Robust PCA on Graphs, in: IEEE Journal of Selected Topics in Signal Processing, April 2016, vol. 10, no 4, pp. 740 - 756. [ DOI : 10.1109/JSTSP.2016.2555239 ]

    https://hal.inria.fr/hal-01277624
  • 20N. Shahid, N. Perraudin, G. Puy, P. Vandergheynst.

    Compressive PCA for Low-Rank Matrices on Graphs, in: IEEE transactions on Signal and Information Processing over Networks, 2016, 17 p, Titled changed from initial preprint "Compressive PCA on graphs". [ DOI : 10.1109/TSIPN.2016.2631890 ]

    https://hal.inria.fr/hal-01277625
  • 21Y. 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
  • 22N. Tremblay, P. Borgnat.

    Subgraph-based filterbanks for graph signals, in: IEEE Transactions on Signal Processing, March 2016.

    https://hal.archives-ouvertes.fr/hal-01243889
  • 23M. B. Wakin, R. Gribonval, V. Koivunen, J. Romberg, J. Wright.

    Introduction to the Issue on Structured Matrices in Signal and Data Processing, in: IEEE Journal of Selected Topics in Signal Processing, May 2016, vol. 10, no 4, pp. 605–607. [ DOI : 10.1109/JSTSP.2016.2553398 ]

    https://hal.inria.fr/hal-01421797

Invited Conferences

  • 24F. Bimbot.

    Towards an Information-Theoretic Framework for Music Structure, in: Dagstuhl Seminar on Computational Music Structure Analysis, Dagstuhk, Germany, February 2016, pp. 167-168. [ DOI : 10.4230/DagRep.6.2.147 ]

    https://hal.archives-ouvertes.fr/hal-01421013
  • 25A. Deleforge, F. Forbes.

    Rectified binaural ratio: A complex T-distributed feature for robust sound localization, in: European Signal Processing Conference, Budapest, Hungary, August 2016, pp. 1257-1261.

    https://hal.inria.fr/hal-01372337
  • 26C. Gaultier, S. Kataria, A. Deleforge.

    VAST : The Virtual Acoustic Space Traveler Dataset, in: International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA), Grenoble, France, February 2017.

    https://hal.archives-ouvertes.fr/hal-01416508
  • 27N. Keriven, N. Tremblay, Y. Traonmilin, R. Gribonval.

    Compressive K-means, in: International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, United States, March 2017.

    https://hal.inria.fr/hal-01386077

International Conferences with Proceedings

  • 28N. Bertin, E. Camberlein, E. Vincent, R. Lebarbenchon, S. Peillon, É. Lamandé, S. Sivasankaran, F. Bimbot, I. Illina, A. Tom, S. Fleury, E. Jamet.

    A French corpus for distant-microphone speech processing in real homes, in: Interspeech 2016, San Francisco, United States, September 2016.

    https://hal.inria.fr/hal-01343060
  • 29N. Bertin, S. Kitić, R. Gribonval.

    Joint estimation of sound source location and boundary impedance with physics-driven cosparse regularization, in: ICASSP - 41st IEEE International Conference on Acoustics, Speech and Signal Processing, Shanghai, China, March 2016.

    https://hal.archives-ouvertes.fr/hal-01247227
  • 30H. Jain, P. Pérez, R. Gribonval, J. Zepeda, H. Jégou.

    Approximate search with quantized sparse representations, in: 14th European Conference on Computer Vision (ECCV), Amsterdam, Netherlands, October 2016.

    https://hal.archives-ouvertes.fr/hal-01361953
  • 31N. 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
  • 32L. 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
  • 33C. 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
  • 34A. 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
  • 35A. 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
  • 36A. 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
  • 37T. Nowakowski, N. Bertin, R. Gribonval, J. De Rosny, L. Daudet.

    Membrane Shape And Boundary Conditions Estimation Using Eigenmode Decomposition, in: ICASSP 2016 – 41st IEEE International Conference on Acoustics, Speech and Signal Processing, Shanghai, China, March 2016.

    https://hal.inria.fr/hal-01254882
  • 38A. 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
  • 39N. Tremblay, G. Puy, P. Borgnat, R. Gribonval, P. Vandergheynst.

    Accelerated spectral clustering using graph filtering of random signals, in: 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), Shanghai, China, March 2016.

    https://hal.archives-ouvertes.fr/hal-01243682
  • 40N. Tremblay, G. Puy, R. Gribonval, P. Vandergheynst.

    Compressive Spectral Clustering, in: 33rd International Conference on Machine Learning, New York, United States, June 2016.

    https://hal.archives-ouvertes.fr/hal-01320214

National Conferences with Proceedings

  • 41M. Chafii, J. Palicot, R. Gribonval.

    La modulation en ondelettes: une modulation alternative à faible consommation d'énergie, in: URSI Énergie et radiosciences, Rennes, France, Journées Scientifiques URSI "Énergie et radiosciences", March 2016, no 143.

    https://hal.archives-ouvertes.fr/hal-01401604
  • 42N. Montavont, D. Shehadeh, J. Palicot, X. Lagrange, A. Blanc, R. Gribonval, P. Mary, J.-Y. Baudais, J.-F. Hélard, M. Crussière, Y. Louët, C. Moy.

    Toward Energy Proportional Networks, in: Journées scientifiques, URSI 2016, Rennes, France, March 2016.

    https://hal.archives-ouvertes.fr/hal-01297894

Conferences without Proceedings

  • 43M. Chafii, M. Lamarana Diallo, J. Palicot, F. Bader, R. Gribonval.

    Adaptive Tone Reservation for better BER Performance in a Frequency Selective Fading Channel, in: IEEE VTC2016-Spring, Nanjing, China, May 2016.

    https://hal-centralesupelec.archives-ouvertes.fr/hal-01290918
  • 44S. Kitic, N. Bertin, R. Gribonval.

    The best of both worlds: synthesis-based acceleration for physics-driven cosparse regularization, in: iTwist 2016 - International Traveling Workshop on Interactions Between Sparse Models and Technology, Aalborg, Denmark, August 2016.

    https://hal.archives-ouvertes.fr/hal-01329051
  • 45E. Perthame, F. Forbes, B. Olivier, A. Deleforge.

    Non linear robust regression in high dimension, in: The XXVIIIth International Biometric Conference, Victoria, Canada, July 2016.

    https://hal.archives-ouvertes.fr/hal-01423622
  • 46E. Perthame, F. Forbes, B. Olivier, A. Deleforge.

    Regression non lineaire robuste en grande dimension, in: 48èmes Journées de Statistique organisées par la Société Française de Statistique, Montpellier, France, May 2016.

    https://hal.archives-ouvertes.fr/hal-01423630

Internal Reports

  • 47C. Louboutin, F. Bimbot.

    Tensorial Description of Chord Progressions: Complementary Scientific Material, IRISA, équipe PANAMA, May 2016.

    https://hal.archives-ouvertes.fr/hal-01314493
  • 48G. Sargent, F. Bimbot, E. Vincent.

    Supplementary material to the article: Estimating the structural segmentation of popular music pieces under regularity constraints, IRISA-Inria, Campus de Beaulieu, 35042 Rennes cedex ; Inria Nancy, équipe Multispeech, September 2016.

    https://hal.inria.fr/hal-01368683

Patents

  • 49M. 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

Other Publications

  • 50A. Deleforge, Y. Traonmilin.

    Phase Unmixing : Multichannel Source Separation with Magnitude Constraints, September 2016, working paper or preprint.

    https://hal.inria.fr/hal-01372418
  • 51S. Kataria, C. Gaultier, A. Deleforge.

    Hearing in a shoe-box : binaural source position and wall absorption estimation using virtually supervised learning , September 2016, working paper or preprint.

    https://hal.inria.fr/hal-01372435
  • 52N. Keriven, A. Bourrier, R. Gribonval, P. Pérez.

    Sketching for Large-Scale Learning of Mixture Models, June 2016, working paper or preprint.

    https://hal.inria.fr/hal-01329195
  • 53L. Le Magoarou, R. Gribonval, N. Tremblay.

    Approximate Fast Fourier Transforms on graphs via multi-layer sparse approximations, December 2016, working paper or preprint.

    https://hal.inria.fr/hal-01416110
  • 54E. Perthame, F. Forbes, A. Deleforge.

    Inverse regression approach to robust non-linear high-to-low dimensional mapping, July 2016, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01347455
References in notes
  • 55A. 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
  • 56L. 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
  • 57S. Arberet, A. Ozerov, F. Bimbot, R. Gribonval.

    A tractable framework for estimating and combining spectral source models for audio source separation, in: Signal Processing, August 2012, vol. 92, no 8, pp. 1886-1901.

    http://hal.inria.fr/hal-00694071
  • 58C. Bilen, S. Kitić, N. Bertin, R. Gribonval.

    Sparse Acoustic Source Localization with Blind Calibration for Unknown Medium Characteristics, August 2014, iTwist - 2nd international - Traveling Workshop on Interactions between Sparse models and Technology.

    https://hal.inria.fr/hal-01060320
  • 59C. Blandin, A. Ozerov, E. Vincent.

    Multi-source TDOA estimation in reverberant audio using angular spectra and clustering, in: Signal Processing, March 2012, vol. 92, pp. 1950-1960, Revised version including minor corrections in equations (17), (18) and Figure 1 compared to the version published by Elsevier. [ DOI : 10.1016/j.sigpro.2011.10.032 ]

    http://hal.inria.fr/inria-00630994
  • 60A. Bourrier.

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

    https://tel.archives-ouvertes.fr/tel-01023030
  • 61A. 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
  • 62A. 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
  • 63A. 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
  • 64M. Chafii.

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

    https://hal.archives-ouvertes.fr/tel-01399509
  • 65M. 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
  • 66M. 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
  • 67M. 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
  • 68M. 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
  • 69F. Chaumette, S. Hutchinson.

    Visual servo control, Part I: Basic approaches, in: IEEE Robotics and Automation Magazine, 2006, vol. 13, no 4, pp. 82-90.

    https://hal.inria.fr/inria-00350283
  • 70A. 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
  • 71N. Duong, E. Vincent, R. Gribonval.

    Spatial location priors for Gaussian model-based reverberant audio source separation, Inria, September 2012, no RR-8057.

    http://hal.inria.fr/hal-00727781
  • 72N. Duong, E. Vincent, R. Gribonval.

    Spatial location priors for Gaussian model based reverberant audio source separation, in: EURASIP Journal on Advances in Signal Processing, September 2013, 149 p. [ DOI : 10.1186/1687-6180-2013-149 ]

    http://hal.inria.fr/hal-00865125
  • 73R. 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
  • 74N. Ito.

    Robust microphone array signal processing against diffuse noise, University of Tokyo, January 2012.

    http://hal.inria.fr/tel-00691931
  • 75N. Ito, E. Vincent, N. Ono, S. Sagayama.

    Robust estimation of directions-of-arrival in diffuse noise based on matrix-space sparsity, Inria, October 2012, no RR-8120.

    http://hal.inria.fr/hal-00746271
  • 76N. Keriven, R. Gribonval.

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

    https://hal.inria.fr/hal-01165984
  • 77S. 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
  • 78S. 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
  • 79S. 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
  • 80S. 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
  • 81S. Kitić.

    Cosparse regularization of physics-driven inverse problems, Université Rennes 1 ; Inria Rennes Bretagne Atlantique, November 2015.

    https://hal.archives-ouvertes.fr/tel-01237323
  • 82M. 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
  • 83L. 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
  • 84L. 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
  • 85L. Le Magoarou.

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

    https://tel.archives-ouvertes.fr/tel-01412558
  • 86A. Magassouba, N. Bertin, F. Chaumette.

    Sound-based control with two microphones, in: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IROS'15, Hamburg, Germany, September 2015, pp. 5568-5573.

    https://hal.inria.fr/hal-01185841
  • 87S. 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
  • 88A. A. Nugraha, A. Liutkus, E. Vincent.

    Multichannel music separation with deep neural networks, in: 24th European Signal Processing Conference (EUSIPCO 2016), 2016, pp. 1748–1752.
  • 89A. 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.
  • 90G. Puy, M. E. Davies, R. Gribonval.

    Linear embeddings of low-dimensional subsets of a Hilbert space to m, in: EUSIPCO - 23rd European Signal Processing Conference, Nice, France, August 2015.

    https://hal.inria.fr/hal-01116153
  • 91G. Puy, M. E. Davies, R. Gribonval.

    Recipes for stable linear embeddings from Hilbert spaces to m, September 2015, Submitted to IEEE Transactions on Information Theory.

    https://hal.inria.fr/hal-01203614
  • 92Y. 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