← Authors

Kimon Antonakopoulos

19 papers · 2019–2025 · 5 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (15) 🧭 Keyword Pioneer 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (6) πŸ—ΊοΈ Taxonomy Completionist (19) 🀝 Dynamic Duo (12) πŸ”₯ Unstoppable (7) πŸ’Ž Century Club (19) πŸ—ƒοΈ Keyword Collector (54) ⚑ Prolific Year (5)

Conferences

NIPS (7) ICML (6) ICLR (4) COLT (1) JMLR (1)

Top co-authors

Volkan Cevher (12) Panayotis Mertikopoulos (10) Ali Kavis (5) Thomas Pethick (3) Ali Ramezani-Kebrya (3) Yu-Guan Hsieh (2) Wanyun Xie (2) Veronica Belmega (2) Dong Quan Vu (2) Zhengqing Wu (1)

Keywords

stochastic optimization (4) convex optimization (3) bregman divergence (2) variational inequality (2) no-regret learning (2) convergence rate (2) first-order method (2) variationally stable game (2) non-convex optimization (2) monotone operator (2) oracle complexity (1) nash equilibrium (1) black-box optimization (1) dual averaging (1) learning theory (1) regret minimization (1) adaptive learning (1) second-order optimization (1) accelerated gradient (1) optimization theory (1)

Papers

Training Deep Learning Models with Norm-Constrained LMOs ICML 2025
Layer-wise Quantization for Quantized Optimistic Dual Averaging ICML 2025
Improving SAM Requires Rethinking its Optimization Formulation ICML 2024
On the Generalization of Stochastic Gradient Descent with Momentum JMLR 2024
Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness ICLR 2024
Universal Gradient Methods for Stochastic Convex Optimization ICML 2024
Distributed Extra-gradient with Optimal Complexity and Communication Guarantees ICLR 2023
Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods NIPS 2022
UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees ICML 2022
Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization NIPS 2022
AdaGrad Avoids Saddle Points ICML 2022
No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation NIPS 2022
Adaptive Extra-Gradient Methods for Min-Max Optimization and Games ICLR 2021
Sifting through the noise: Universal first-order methods for stochastic variational inequalities NIPS 2021
Fast Routing under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights NIPS 2021
Adaptive First-Order Methods Revisited: Convex Minimization without Lipschitz Requirements NIPS 2021
Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium COLT 2021
Online and stochastic optimization beyond Lipschitz continuity: A Riemannian approach ICLR 2020
An adaptive Mirror-Prox method for variational inequalities with singular operators NIPS 2019