King Abdullah University of Science and Technology (KAUST), Saudi Arabia
Laurent Condat

Senior Research Scientist

Visual Computing Center
Building 1 (West), Office 2118



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Optimization for data science: algorithms, convex relaxations, sparse and low rank models, inverse problems, image and signal processing, learning

                  
 

About me: I got my PhD in 2006 from Grenoble Inst. of Tech., Grenoble, France. After 2 years as a postdoc in Munich, Germany, I was hired as a permanent researcher by the CNRS in 2008. I spent 4 years in the GREYC, Caen, and 7 years in GIPSA-Lab, Grenoble. Since Nov. 2019, I am on leave from the CNRS and I am a researcher in the Visual Computing Center of KAUST.


News

[July 22] Our paper "RandProx: Primal-Dual Optimization Algorithms with Randomized Proximal Updates" is on arXiv.

[July 22] I have been promoted to Senior Research Scientist.

[June 22] Our paper "MURANA: A Generic Framework for Stochastic Variance-Reduced Optimization" has been accepted at MSML 2022.

[May 22] My paper "Tikhonov regularization of circle-valued signals" has been accepted to IEEE Transactions on Signal Processing.

[May 22] Our paper "Dualize, split, randomize: Fast nonsmooth optimization algorithms" has been accepted to Journal of Optimization Theory and Applications.

[May 22] Our paper "EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization", written earlier this year, is on arXiv.

[Apr. 22] Our tutorial paper "Proximal Splitting Algorithms for Convex Optimization: A Tour of Recent Advances, with New Twists" has been accepted to SIAM Review.

[Jan. 22] Our paper "Distributed Proximal Splitting Algorithms with Rates and Acceleration" has been published in Frontiers in Signal Processing.  Link

[Jan. 22] Our paper "An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints" accepted at AISTATS 2022.

[Dec. 21] Our tutorial paper has been revised, again. The title has changed to "Proximal Splitting Algorithms for Convex Optimization: A Tour of Recent Advances, with New Twists".

[Nov. 21] Daniele Picone, whose work I co-supervised with Mauro Dalla Mura, defended his PhD. Congratulations Daniele!

[Apr. 21] I have been appointed as an Associate Editor for IEEE Transactions on Signal Processing.

[Feb. 21] Julien Baderot, whose work I co-supervised with Michel Desvignes and Mauro Dalla Mura, defended his PhD. Congratulations Julien!

[Nov. 20] 3 papers accepted for presentation: 2 at the NeurIPS Workshop on Optimization for Machine Learning (OPT2020) and 1 at the NeurIPS Workshop on Scalability, Privacy, and Security in Federated Learning (SpicyFL 2020).

[Oct. 20] 2 new papers on arXiv: the paper "Distributed Proximal Splitting Algorithms with Rates and Acceleration" and the paper "Optimal Gradient Compression for Distributed and Federated Learning".

[Oct. 20] Our overview paper on proximal splitting, with new relaxation results, has been revised. The title has been changed from "Splitting Algorithms: Relax them all!" to "Proximal Splitting Algorithms: A Tour of Recent Advances, with New Twists".

[July 20] My paper "Atomic norm minimization for decomposition into complex exponentials and optimal transport in Fourier domain" accepted to Journal of Approximation Theory.   Link

[June 20] Our paper "From local SGD to local fixed point methods for federated learning" accepted at ICML 2020.  Link

[May 20] Our paper on optical tomography was chosen for the cover of the journal Sensors.