← Authors

Nicolas Loizou

20 papers · 2019–2025 · 4 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (4) πŸƒ Academic Marathon (6) 🐝 Cross-Pollinator (7) πŸ—ΊοΈ Taxonomy Completionist (22) πŸ† Keyword Champion (3) πŸ”¬ Deep Specialist (10) 🧬 Topic Evolution πŸ”₯ Unstoppable (7) πŸ—ƒοΈ Keyword Collector (61) πŸ’Ž Century Club (20)

Conferences

AISTATS (7) NIPS (5) ICLR (4) ICML (4)

Top co-authors

Eduard Gorbunov (5) Simon Lacoste-Julien (4) Gauthier Gidel (4) Hugo Berard (4) Sayantan Choudhury (3) Ioannis Mitliagkas (3) Dimitris Oikonomou (2) Samuel Sokota (1) Issam Hadj Laradji (1) Paul Zhang (1)

Keywords

variational inequality (6) convergence analysis (6) stochastic gradient descent (6) stochastic optimization (5) convergence rate (5) extragradient method (4) min-max optimization (3) stochastic extragradient (3) minimax optimization (2) distributed learning (2) bilinear game (2) gossip algorithm (2) convergence guarantee (2) smooth game (2) neural network optimization (1) convex optimization (1) decentralized optimization (1) nonconvex optimization (1) adaptive learning rate (1) medical imaging (1)

Papers

Sharpness-Aware Minimization: General Analysis and Improved Rates ICLR 2025
Stochastic Polyak Step-sizes and Momentum: Convergence Guarantees and Practical Performance ICLR 2025
Stochastic Extragradient with Random Reshuffling: Improved Convergence for Variational Inequalities AISTATS 2024
Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad NIPS 2024
Enhancing vision-language models for medical imaging: bridging the 3D gap with innovative slice selection NIPS 2024
Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates ICLR 2024
A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games ICLR 2023
Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions NIPS 2023
Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods AISTATS 2023
On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging AISTATS 2022
Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution NIPS 2022
Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity AISTATS 2022
Stochastic Extragradient: General Analysis and Improved Rates AISTATS 2022
Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity NIPS 2021
Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence AISTATS 2021
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation AISTATS 2021
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates ICML 2020
Stochastic Hamiltonian Gradient Methods for Smooth Games ICML 2020
Stochastic Gradient Push for Distributed Deep Learning ICML 2019
SGD: General Analysis and Improved Rates ICML 2019