Homepage

I am a Google Research Fellow at the Simons Institute, UC Berkeley, USA.

Previously, I was a Postdoctoral Fellow at KAUST, Saudi Arabia, hosted by Peter Richtárik. I did my Ph.D at Telecom Paris and Paris–Saclay University, France, under the supervision of Pascal Bianchi and Walid Hachem.

I use optimization, statistics, optimal transport, convex analysis etc. to study machine learning algorithms. I received the Masters degrees in 2015 from ENSAE Paris, where I studied statistics, and from Paris–Saclay University, where I studied probability theory. Here is my CV.

News

• I will join the Machine Learning Foundations group at Microsoft Research Redmond as a Senior Researcher in 2022.

Selected papers

Sampling and optimal transport

• Adil Salim, Lukang Sun, Peter Richtárik, “Complexity Analysis of Stein Variational Gradient Descent Under Talagrand’s Inequality T1”, June 2021.

• Anna Korba, Adil Salim, Michael Arbel, Giulia Luise and Arthur Gretton, “A Non-Asymptotic Analysis for Stein Variational Gradient Descent”, NeurIPS 2020.

• Adil Salim and Peter Richtárik, “Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm”, NeurIPS 2020.

• Adil Salim, Anna Korba and Giulia Luise, “The Wasserstein Proximal Gradient Algorithm”, NeurIPS 2020.

• Adil Salim, Dmitry Kovalev and Peter Richtárik, “Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates”, Spotlight @ NeurIPS 2019, Vancouver, Canada.

• Michael Arbel, Anna Korba, Adil Salim and Arthur Gretton, “Maximum Mean Discrepancy Gradient Flow”, NeurIPS 2019, Vancouver, Canada.

Optimization and monotone operators

• Adil Salim, Laurent Condat, Dmitry Kovalev and Peter Richtárik, “An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints”, February 2021.

• Dmitry Kovalev, Adil Salim and Peter Richtárik, “Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization”, NeurIPS 2020.

• Adil Salim, A Strong Law of Large Numbers for Random Monotone Operators, October 2019.

• Pascal Bianchi, Walid Hachem and Adil Salim, A Fully Stochastic Primal-Dual Algorithm, Optimization Letters, June 2020.

• Pascal Bianchi, Walid Hachem, and Adil Salim, Constant Step Stochastic Approximations Involving Differential Inclusions: Stability, Long-Run Convergence and Applications, Stochastics, May 2018.

• Adil Salim, Pascal Bianchi, and Walid Hachem, Snake: a Stochastic Proximal Gradient Algorithm for Regularized Problems over Large Graphs, Transaction on Automatic Control, March 2018.

• Pascal Bianchi, Walid Hachem, and Adil Salim, A constant step Forward-Backward algorithm involving random maximal monotone operators, Journal of Convex Analysis, March 2018.