Adil Salim

Orcid: 0000-0002-3829-8864

According to our database1, Adil Salim authored at least 30 papers between 2016 and 2024.

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Bibliography

2024
Federated Sampling with Langevin Algorithm under Isoperimetry.
Trans. Mach. Learn. Res., 2024

Long-time asymptotics of noisy SVGD outside the population limit.
CoRR, 2024

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.
CoRR, 2024

2023
Gaussian random field approximation via Stein's method with applications to wide random neural networks.
CoRR, 2023

Textbooks Are All You Need.
CoRR, 2023

Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space.
CoRR, 2023

The probability flow ODE is provably fast.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space.
Proceedings of the International Conference on Machine Learning, 2023

Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

On the complexity of finding stationary points of smooth functions in one dimension.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022
Dualize, Split, Randomize: Toward Fast Nonsmooth Optimization Algorithms.
J. Optim. Theory Appl., 2022

Federated Learning with a Sampling Algorithm under Isoperimetry.
CoRR, 2022

A Convergence Theory for SVGD in the Population Limit under Talagrand's Inequality T1.
Proceedings of the International Conference on Machine Learning, 2022

Improved analysis for a proximal algorithm for sampling.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
A fully stochastic primal-dual algorithm.
Optim. Lett., 2021

Complexity Analysis of Stein Variational Gradient Descent Under Talagrand's Inequality T1.
CoRR, 2021

2020
Dualize, Split, Randomize: Fast Nonsmooth Optimization Algorithms.
CoRR, 2020

Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The Wasserstein Proximal Gradient Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Non-Asymptotic Analysis for Stein Variational Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Snake: A Stochastic Proximal Gradient Algorithm for Regularized Problems Over Large Graphs.
IEEE Trans. Autom. Control., 2019

Distributed Fixed Point Methods with Compressed Iterates.
CoRR, 2019

Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Maximum Mean Discrepancy Gradient Flow.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
A Constant Step Stochastic Douglas-Rachford Algorithm with Application to non Separable Regularizations.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017
An adaptive distributed asynchronous algorithm with application to target localization.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2016
A stochastic proximal point algorithm for total variation regularization over large scale graphs.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016


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