, Static and Dynamic Source Separation Using Nonnegative Factorizations: A unified view, IEEE Signal Processing Magazine, vol.31, issue.3, pp.66-75, 2014.
DOI : 10.1109/MSP.2013.2297715
, Monaural Sound Source Separation by Nonnegative Matrix Factorization With Temporal Continuity and Sparseness Criteria, IEEE Transactions on Audio, Speech and Language Processing, vol.15, issue.3, pp.1066-1074, 2007.
DOI : 10.1109/TASL.2006.885253
, Multichannel Nonnegative Matrix Factorization in Convolutive Mixtures for Audio Source Separation, IEEE Transactions on Audio, Speech, and Language Processing, vol.18, issue.3, pp.550-563, 2010.
DOI : 10.1109/TASL.2009.2031510
, Analysis versus synthesis in signal priors, Inverse Problems, vol.23, issue.3, p.947, 2007.
DOI : 10.1088/0266-5611/23/3/007
URL : http://www.cs.technion.ac.il/%7Eronrubin/Publications/eusipco_avs.pdf
, Adapted and Adaptive Linear Time-Frequency Representations: A Synthesis Point of View, IEEE Signal Processing Magazine, vol.30, issue.6, pp.20-31, 2013.
DOI : 10.1109/MSP.2013.2266075
URL : https://hal.archives-ouvertes.fr/hal-00863907
, Supervised sparse analysis and synthesis operators, Advances in Neural Information Processing Systems, pp.908-916, 2013.
, The cosparse analysis model and algorithms, Applied and Computational Harmonic Analysis, vol.34, issue.1, pp.30-56, 2013.
DOI : 10.1016/j.acha.2012.03.006
URL : https://hal.archives-ouvertes.fr/inria-00602205
, Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music Analysis, Neural Computation, vol.14, issue.3, pp.793-830, 2009.
DOI : 10.1016/j.sigpro.2007.01.024
, Low-rank time-frequency synthesis Available: https://www.irit.fr/ ? Cedric.Fevotte/ publications/proceedings/nips14.pdf [10] ?? Hybrid sparse and low-rank time-frequency signal decomposition Available: https: //www.irit.fr/ ? Cedric Learning the parts of objects with nonnegative matrix factorization, Advances in Neural Information Processing Systems (NIPS) Proc. European Signal Processing Conference (EUSIPCO), pp.788-791, 1999.
, Sparse Bayesian learning and the relevance vector machine, Journal of Machine Learning Research, vol.1, pp.211-244, 2001.
, Sparse Bayesian Learning for Basis Selection, IEEE Transactions on Signal Processing, vol.52, issue.8, pp.2153-2164, 2004.
DOI : 10.1109/TSP.2004.831016
URL : http://dsp.rice.edu/files/cs/Rao8.pdf
, An EM algorithm for wavelet-based image restoration, IEEE Transactions on Image Processing, vol.12, issue.8, pp.906-916, 2003.
DOI : 10.1109/TIP.2003.814255
URL : http://cmc.rice.edu/docs/docs/Fig2002May1ImageResto.ps
, A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems, SIAM Journal on Imaging Sciences, vol.2, issue.1, pp.183-202, 2009.
DOI : 10.1137/080716542
, A wavelet-based regularized reconstruction algorithm for SENSE parallel MRI with applications to neuroimaging???, Medical Image Analysis, vol.15, issue.2, pp.185-201, 2011.
DOI : 10.1016/j.media.2010.08.001
, A Majorize-Minimize Memory Gradient method for complex-valued inverse problems, Signal Processing, vol.103, pp.285-295, 2014.
DOI : 10.1016/j.sigpro.2013.09.026
URL : https://hal.archives-ouvertes.fr/hal-00829788
, On the Convergence of the Iterates of the ???Fast Iterative Shrinkage/Thresholding Algorithm???, Journal of Optimization Theory and Applications, vol.155, issue.2, pp.968-982, 2015.
DOI : 10.1007/978-1-4419-9467-7
, Algorithms for Nonnegative Matrix Factorization with the ??-Divergence, Neural Computation, vol.11, issue.9, pp.2421-2456, 2011.
DOI : 10.1109/TASL.2009.2034186
, Complex SVD initialization for NMF source separation on audio spectrograms, Proc. Deutsche Jahrestagung für Akustik (DAGA), 2015.
, Fixed-Point Continuation for $\ell_1$-Minimization: Methodology and Convergence, SIAM Journal on Optimization, vol.19, issue.3, pp.1107-1130, 2008.
DOI : 10.1137/070698920
, The large time-frequency analysis toolbox 2.0, Sound, Music, and Motion, pp.419-442, 2014.
, Multi-resolution signal decomposition with time-domain spectrogram factorization, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), p.2015
DOI : 10.1109/ICASSP.2015.7177937
, Gaussian Processes for Underdetermined Source Separation, IEEE Transactions on Signal Processing, vol.59, issue.7, pp.3155-3167, 2011.
DOI : 10.1109/TSP.2011.2119315
URL : https://hal.archives-ouvertes.fr/hal-00643951
, Infinite positive semidefinite tensor factorization for source separation of mixture signals, Proc. International Conference on Machine Learning (ICML), pp.576-584, 2013.
, Time-Frequency Analysis as Probabilistic Inference, IEEE Transactions on Signal Processing, vol.62, issue.23, pp.6171-6183, 2014.
DOI : 10.1109/TSP.2014.2362100
URL : http://doi.org/10.1109/tsp.2014.2362100
, Singing-voice separation from monaural recordings using robust principal component analysis, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.57-60, 2012.
DOI : 10.1109/ICASSP.2012.6287816
, Speech enhancement by sparse, low-rank, and dictionary spectrogram decomposition, 2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2013.
DOI : 10.1109/WASPAA.2013.6701883
, A novel speech enhancement method based on constrained low-rank and sparse matrix decomposition, Speech Communication, vol.60, pp.44-55, 2014.
DOI : 10.1016/j.specom.2014.03.002
, Robust principal component analysis?, Journal of the ACM, vol.58, issue.3, pp.1-37, 2009.
DOI : 10.1145/1970392.1970395
, Hybrid representations for audiophonic signal encoding, Signal Processing, vol.82, issue.11, pp.1595-1617, 2002.
DOI : 10.1016/S0165-1684(02)00304-3
URL : https://hal.archives-ouvertes.fr/hal-01300317
, Morphological component analysis, Wavelets XI, pp.59-140, 2005.
DOI : 10.1117/12.615237
URL : https://hal.archives-ouvertes.fr/hal-00090691
, Sparse regression using mixed norms, Applied and Computational Harmonic Analysis, vol.27, issue.3, pp.303-324, 2009.
DOI : 10.1016/j.acha.2009.05.006
URL : https://hal.archives-ouvertes.fr/hal-00202904
, Compressive sampling of nonnegative signals PLACE PHOTO HERE Cédric Févotte is a CNRS senior researcher at Institut de Recherche en Informatique de Toulouse (IRIT) Previously, he has been a CNRS researcher at Laboratoire Lagrange (Nice, 2013-2016) & Télécom ParisTech) and a postdoc at University of Cambridge He holds MEng and PhD degrees in EECS fromÉcolefrom´fromÉcole Centrale de Nantes. His research interests concern statistical signal processing and machine learning, for inverse problems and source separation. He is a member of the IEEE Machine Learning for Signal Processing technical committee and an associate editor for the IEEE Transactions on Signal Processing, Proc. IEEE Workshop on Machine Learning for Signal Processing Mist- Technologies (the startup that became Audionamix 2014, he was the co-recipient of an IEEE Signal Processing Society Best Paper Award for his work on audio source separation using multichannel nonnegative matrix factorization. He is the principal investigator of the European Research Council project FACTORY (New paradigms for latent factor estimation, pp.2016-2021, 2003.