Kimon Antonakopoulos
19 papers · 2019–2025 · 5 venues · across top CS/AI venues
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Venues
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Research topics
Keywords
stochastic optimization
(5)
convergence rate
(4)
convex optimization
(3)
variational inequality
(3)
no-regret learning
(2)
non-convex optimization
(2)
variationally stable game
(2)
regret bound
(2)
first-order method
(2)
monotone operator
(2)
bregman divergence
(2)
mirror descent
(2)
regret minimization
(1)
sharpness-aware minimization
(1)
black-box optimization
(1)
adaptive learning
(1)
distributed learning
(1)
stochastic gradient
(1)
accelerated optimization
(1)
smooth optimization
(1)
Papers
Layer-wise Quantization for Quantized Optimistic Dual Averaging
ICML 2025
Training Deep Learning Models with Norm-Constrained LMOs
ICML 2025
Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness
ICLR 2024
Improving SAM Requires Rethinking its Optimization Formulation
ICML 2024
On the Generalization of Stochastic Gradient Descent with Momentum
JMLR 2024
Universal Gradient Methods for Stochastic Convex Optimization
ICML 2024
Distributed Extra-gradient with Optimal Complexity and Communication Guarantees
ICLR 2023
AdaGrad Avoids Saddle Points
ICML 2022
Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization
NeurIPS 2022
Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods
NeurIPS 2022
No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation
NeurIPS 2022
UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees
ICML 2022
Adaptive Extra-Gradient Methods for Min-Max Optimization and Games
ICLR 2021
Adaptive First-Order Methods Revisited: Convex Minimization without Lipschitz Requirements
NeurIPS 2021
Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium
COLT 2021
Fast Routing under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights
NeurIPS 2021
Sifting through the noise: Universal first-order methods for stochastic variational inequalities
NeurIPS 2021
Online and stochastic optimization beyond Lipschitz continuity: A Riemannian approach
ICLR 2020
An adaptive Mirror-Prox method for variational inequalities with singular operators
NeurIPS 2019