Loizou, Nicolas

27 publications

NeurIPS 2025 Extragradient Method for $(l_0, L_1)$-Lipschitz Root-Finding Problems Sayantan Choudhury, Nicolas Loizou

NeurIPS 2025 Multiplayer Federated Learning: Reaching Equilibrium with Less Communication TaeHo Yoon, Sayantan Choudhury, Nicolas Loizou

ICLR 2025 Sharpness-Aware Minimization: General Analysis and Improved Rates Dimitris Oikonomou, Nicolas Loizou

ICLR 2025 Stochastic Polyak Step-Sizes and Momentum: Convergence Guarantees and Practical Performance Dimitris Oikonomou, Nicolas Loizou

ICLR 2024 Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates Siqi Zhang, Sayantan Choudhury, Sebastian U Stich, Nicolas Loizou

NeurIPS 2024 Enhancing Vision-Language Models for Medical Imaging: Bridging the 3D Gap with Innovative Slice Selection Yuli Wang, Jian Peng, Yuwei Dai, Craig Jones, Haris Sair, Jinglai Shen, Nicolas Loizou, Jing Wu, Wen-Chi Hsu, Maliha Imami, Zhicheng Jiao, Paul Zhang, Harrison Bai

TMLR 2024 Locally Adaptive Federated Learning Sohom Mukherjee, Nicolas Loizou, Sebastian U Stich

NeurIPS 2024 Remove That Square Root: A New Efficient Scale-Invariant Version of AdaGrad Sayantan Choudhury, Nazarii Tupitsa, Nicolas Loizou, Samuel Horváth, Martin Takáč, Eduard Gorbunov

AISTATS 2024 Stochastic Extragradient with Random Reshuffling: Improved Convergence for Variational Inequalities Konstantinos Emmanouilidis, Rene Vidal, Nicolas Loizou

ICLR 2023 A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games Samuel Sokota, Ryan D'Orazio, J Zico Kolter, Nicolas Loizou, Marc Lanctot, Ioannis Mitliagkas, Noam Brown, Christian Kroer

TMLR 2023 AI-SARAH: Adaptive and Implicit Stochastic Recursive Gradient Methods Zheng Shi, Abdurakhmon Sadiev, Nicolas Loizou, Peter Richtárik, Martin Takáč

NeurIPS 2023 Single-Call Stochastic Extragradient Methods for Structured Non-Monotone Variational Inequalities: Improved Analysis Under Weaker Conditions Sayantan Choudhury, Eduard Gorbunov, Nicolas Loizou

AISTATS 2023 Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods Aleksandr Beznosikov, Eduard Gorbunov, Hugo Berard, Nicolas Loizou

TMLR 2023 Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants via the Mirror Stochastic Polyak Stepsize Ryan D'Orazio, Nicolas Loizou, Issam H. Laradji, Ioannis Mitliagkas

AISTATS 2022 Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections with Cocoercivity Eduard Gorbunov, Nicolas Loizou, Gauthier Gidel

AISTATS 2022 On the Convergence of Stochastic Extragradient for Bilinear Games Using Restarted Iteration Averaging Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael Jordan

AISTATS 2022 Stochastic Extragradient: General Analysis and Improved Rates Eduard Gorbunov, Hugo Berard, Gauthier Gidel, Nicolas Loizou

NeurIPSW 2022 A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games Samuel Sokota, Ryan D'Orazio, J Zico Kolter, Nicolas Loizou, Marc Lanctot, Ioannis Mitliagkas, Noam Brown, Christian Kroer

NeurIPS 2022 Dynamics of SGD with Stochastic Polyak Stepsizes: Truly Adaptive Variants and Convergence to Exact Solution Antonio Orvieto, Simon Lacoste-Julien, Nicolas Loizou

NeurIPSW 2022 ProxSkip for Stochastic Variational Inequalities: A Federated Learning Algorithm for Provable Communication Acceleration Siqi Zhang, Nicolas Loizou

NeurIPSW 2022 Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods Aleksandr Beznosikov, Eduard Gorbunov, Hugo Berard, Nicolas Loizou

AISTATS 2021 SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation Robert Gower, Othmane Sebbouh, Nicolas Loizou

AISTATS 2021 Stochastic Polyak Step-Size for SGD: An Adaptive Learning Rate for Fast Convergence Nicolas Loizou, Sharan Vaswani, Issam Hadj Laradji, Simon Lacoste-Julien

NeurIPS 2021 Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis Under Expected Co-Coercivity Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien

ICML 2020 A Unified Theory of Decentralized SGD with Changing Topology and Local Updates Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian Stich

ICML 2020 Stochastic Hamiltonian Gradient Methods for Smooth Games Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau, Pascal Vincent, Simon Lacoste-Julien, Ioannis Mitliagkas

ICML 2019 Stochastic Gradient Push for Distributed Deep Learning Mahmoud Assran, Nicolas Loizou, Nicolas Ballas, Mike Rabbat