A Unified Evaluation of Iterative Projection Algorithms for Phase Retrieval, Rev. Sci. Instrum, vol.78, pp.11-301, 2007. ,
Phase Retrieval with Application to Optical Imaging: A contemporary overview, IEEE Signal Processing Magazine, vol.32, issue.3, pp.87-109, 2015. ,
DOI : 10.1109/MSP.2014.2352673
On phase retrieval of finite-length sequences using the initial time sample, IEEE Transactions on Circuits and Systems, vol.38, issue.8, pp.954-958, 1991. ,
DOI : 10.1109/31.85639
A practical algorithm for the determination of the phase from image and diffraction plane pictures, Optik, vol.35, issue.2, pp.237-246, 1972. ,
Phase retrieval algorithms: a comparison, Applied Optics, vol.21, issue.15, pp.2758-2769, 1982. ,
DOI : 10.1364/AO.21.002758
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.452.7174
Phase retrieval, error reduction algorithm, and Fienup variants: a view from convex optimization, Journal of the Optical Society of America A, vol.19, issue.7, pp.1334-1345, 2002. ,
DOI : 10.1364/JOSAA.19.001334
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.75.1070
Phase Retrieval via Matrix Completion, SIAM Journal on Imaging Sciences, vol.6, issue.1, pp.199-225, 2013. ,
DOI : 10.1137/110848074
Sparsity based sub-wavelength imaging with partially incoherent light via quadratic compressed sensing, Optics Express, vol.19, issue.16, pp.14-807, 2011. ,
DOI : 10.1364/OE.19.014807
URL : http://arxiv.org/abs/1104.4406
Recovery of sparse 1-D signals from the magnitudes of their Fourier transform, 2012 IEEE International Symposium on Information Theory Proceedings, p.2012 ,
DOI : 10.1109/ISIT.2012.6283508
Compressive Phase Retrieval From Squared Output Measurements Via Semidefinite Programming*, IFAC Proceedings Volumes, vol.45, issue.16, p.2012 ,
DOI : 10.3182/20120711-3-BE-2027.00415
URL : http://arxiv.org/abs/1111.6323
Phase recovery, MaxCut and complex semidefinite programming, Mathematical Programming, vol.16, issue.3, pp.47-81, 2015. ,
DOI : 10.1007/s10107-013-0738-9
URL : https://hal.archives-ouvertes.fr/hal-00907535
Phase Retrieval via Wirtinger Flow: Theory and Algorithms, IEEE Transactions on Information Theory, vol.61, issue.4, 2014. ,
DOI : 10.1109/TIT.2015.2399924
Optimal rates of convergence for noisy sparse phase retrieval via thresholded Wirtinger flow, The Annals of Statistics, vol.44, issue.5, p.2015 ,
DOI : 10.1214/16-AOS1443
GESPAR: Efficient Phase Retrieval of Sparse Signals, IEEE Transactions on Signal Processing, vol.62, issue.4, pp.928-938, 2014. ,
DOI : 10.1109/TSP.2013.2297687
Compressive phase retrieval, Wavelets XII, pp.670-120, 2007. ,
DOI : 10.1117/12.736360
A Mathematical Introduction to Compressive Sensing, ser. Applied and Numerical Harmonic Analysis, 2013. ,
DOI : 10.1007/978-0-8176-4948-7
Sampling Theory ? Beyond Bandlimited Systems, 2015. ,
DOI : 10.1109/msp.2009.932125
Emergence of simple-cell receptive field properties by learning a sparse code for natural images, Nature, vol.381, issue.6583, pp.607-609, 1996. ,
DOI : 10.1038/381607a0
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries, IEEE Transactions on Image Processing, vol.15, issue.12, pp.3736-3745, 2006. ,
DOI : 10.1109/TIP.2006.881969
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.109.6477
Sparse Modeling for Image and Vision Processing, Trends Comp. Graphics and Vision, pp.85-283, 2014. ,
DOI : 10.1561/0600000058
URL : https://hal.archives-ouvertes.fr/hal-01081139
<tex>$rm K$</tex>-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation, IEEE Transactions on Signal Processing, vol.54, issue.11, pp.4311-4322, 2006. ,
DOI : 10.1109/TSP.2006.881199
Online learning for matrix factorization and sparse coding, J. Mach. Learn. Res, vol.11, pp.19-60, 2010. ,
URL : https://hal.archives-ouvertes.fr/inria-00408716
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
Dictionary learning from phaseless measurements, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.2016-4702 ,
DOI : 10.1109/ICASSP.2016.7472569
URL : https://hal.archives-ouvertes.fr/hal-01387416
Hybrid projection???reflection method for phase retrieval, Journal of the Optical Society of America A, vol.20, issue.6, pp.1025-1034, 2003. ,
DOI : 10.1364/JOSAA.20.001025
Relaxed averaged alternating reflections for diffraction imaging, Inverse Problems, vol.21, issue.1, pp.37-50, 2005. ,
DOI : 10.1088/0266-5611/21/1/004
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems, Communications on Pure and Applied Mathematics, vol.28, issue.1-2, p.2015 ,
DOI : 10.1007/s10107-013-0738-9
Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing, 2010. ,
DOI : 10.1007/978-1-4419-7011-4
Atomic Decomposition by Basis Pursuit, SIAM Journal on Scientific Computing, vol.20, issue.1, pp.33-61, 1998. ,
DOI : 10.1137/S1064827596304010
On the Computational Intractability of Exact and Approximate Dictionary Learning, IEEE Signal Processing Letters, vol.22, issue.1, pp.45-49, 2015. ,
DOI : 10.1109/LSP.2014.2345761
On the convergence properties of the projected gradient method for convex optimization, Comput. Appl. Math, vol.22, issue.1, pp.37-52, 2003. ,
A coordinate gradient descent method for nonsmooth separable minimization, Mathematical Programming, vol.23, issue.1-2, pp.387-423, 2009. ,
DOI : 10.1007/s10107-007-0170-0
DOLPHIn???Dictionary Learning for Phase Retrieval, IEEE Transactions on Signal Processing, vol.64, issue.24 ,
DOI : 10.1109/TSP.2016.2607180
URL : https://hal.archives-ouvertes.fr/hal-01387428
Image Quality Assessment: From Error Visibility to Structural Similarity, IEEE Transactions on Image Processing, vol.13, issue.4, pp.600-612, 2004. ,
DOI : 10.1109/TIP.2003.819861
Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition, Proceedings of 27th Asilomar Conference on Signals, Systems and Computers, pp.40-44, 1993. ,
DOI : 10.1109/ACSSC.1993.342465
He was with the Institute for Mathematical Optimization at TU Braunschweig from 03, he was an interim professor for mathematical optimization at TU Braunschweig. His research interests are in discrete and continuous optimization, particularly in sparse recovery and compressed sensing, as well as computational complexity, Dr. Tillmann won the Best Student Paper Award at the SPARS conference 2013 in Lausanne, Switzerland. He is a member of the Mathematical Optimization Society (MOS), the International Association of Applied Mathematics and Mechanics (GAMM), and an IEEE Signal Processing Society Affiliate. He serves as a reviewer for IEEE Transactions on Information Theory, IEEE Signal Processing Letters and several other journals, 2009. ,
12) received the B.Sc. degree in Physics in 1995 and the B.Sc. degree in Electrical Engineering in 1996 both from Tel-Aviv University (TAU), Tel-Aviv, Israel, and the Ph, she was a Postdoctoral Fellow at the Digital Signal Processing Group at MIT. She is currently a Professor in the Department of Electrical Engineering at the Technion ? Israel Institute of Technology, from the Massachusetts Institute of Technology (MIT) where she holds the Edwards Chair in Engineering. She is also a Research Affiliate with the Research, 2002. ,