Waldspurger Irène - CV


Waldspurger Irène

CNRS Researcher


Irène Waldspurger obtained a master's degree in fundamental mathematics, then prepared a Phd in signal processing and machine learning at École Normale Supérieure de Paris, under the supervision of Stéphane Mallat. She defended it in 2015 and subsequently spent a year as a postdoctoral fellow at MIT, mentored by Philippe Rigollet. Since 2017, she is chargée de recherche at CNRS, affiliated with Ceremade (Paris Dauphine) and the Inria team Mokaplan.



Waldspurger I., Waters A. (2020), Rank optimality for the Burer-Monteiro factorization, SIAM Journal on Optimization, vol. 30, n°3, p. 2577-2602

Waldspurger I. (2018), Phase retrieval with random Gaussian sensing vectors by alternating projections, IEEE Transactions on Information Theory, vol. 64, n°5, p. 3301-3312

Waldspurger I. (2017), Phase retrieval for wavelet transforms, IEEE Transactions on Information Theory, vol. 63, n°5, p. 2993 - 3009

Fogel F., Waldspurger I., d'Aspremont A. (2016), Phase retrieval for imaging problems, Mathematical Programming Computation, vol. 8, n°3, p. 311–335

Mallat S., Waldspurger I. (2015), Phase retrieval for the Cauchy wavelet transform, Journal of Fourier Analysis and Applications, vol. 21, n°6, p. 1251–1309

Waldspurger I., d'Aspremont A., Mallat S. (2015), Phase recovery, Maxcut and complex semidefinite programming, Mathematical Programming, vol. 149, n°1-2, p. 47-81

Chapitres d'ouvrage

Ammari H., Mallat S., Waldspurger I., Wang H. (2016), Wavelet methods for shape perception in electro-sensing, in Habib Ammari, Yves Capdeboscq, Hyeonbae Kang, Imbo Sim, Imaging, Multi-scale and High Contrast Partial Differential Equations Amsterdam University Press

Communications avec actes

Waldspurger I. (2017), Exponential decay of scattering coefficients, in , 2017 International Conference on Sampling Theory and Applications (SampTA), 3-7 juillet 2017, Tallinn, Estonia, Tallinn, IEEE - Institute of Electrical and Electronics Engineers, 143-146 p.

Prépublications / Cahiers de recherche

Waldspurger I. (2021), Lecture notes on non-convex algorithms for low-rank matrix recovery, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 62 p.

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