← Authors

Adil SALIM

15 papers · 2019–2025 · 6 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) πŸƒ Academic Marathon (6) 🐝 Cross-Pollinator (5) πŸ—ΊοΈ Taxonomy Completionist (21) πŸ‘‘ Triple Crown πŸ’Ž Century Club (15) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (72)

Conferences

NIPS (7) COLT (2) ICLR (2) ICML (2) AISTATS (1) ALT (1)

Top co-authors

Sinho Chewi (6) Peter Richtarik (5) Anna Korba (3) Dmitry Kovalev (3) Michael Arbel (2) Giulia Luise (2) Sitan Chen (2) Krishna Balasubramanian (2) Arthur Gretton (2) Yuanzhi Li (2)

Keywords

gradient descent (3) bayesian inference (3) wasserstein gradient flow (3) wasserstein distance (2) log concave distribution (2) markov chain monte carlo (2) langevin dynamics (2) stein variational gradient descent (2) convergence guarantee (2) langevin algorithm (2) kernel methods (2) kl divergence (2) probability distribution (2) optimal algorithm (2) decentralized optimization (1) communication complexity (1) non-convex optimization (1) optimal transport (1) probability metrics (1) stochastic gradient (1)

Papers

Long-time asymptotics of noisy SVGD outside the population limit ICLR 2025
The probability flow ODE is provably fast NIPS 2023
Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space ICML 2023
Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions ICLR 2023
On the complexity of finding stationary points of smooth functions in one dimension ALT 2023
An Optimal Algorithm for Strongly Convex Minimization under Affine Constraints AISTATS 2022
Towards a Theory of Non-Log-Concave Sampling:First-Order Stationarity Guarantees for Langevin Monte Carlo COLT 2022
Improved analysis for a proximal algorithm for sampling COLT 2022
A Convergence Theory for SVGD in the Population Limit under Talagrand’s Inequality T1 ICML 2022
Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm NIPS 2020
A Non-Asymptotic Analysis for Stein Variational Gradient Descent NIPS 2020
Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized Optimization NIPS 2020
The Wasserstein Proximal Gradient Algorithm NIPS 2020
Maximum Mean Discrepancy Gradient Flow NIPS 2019
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates NIPS 2019