Kimon Antonakopoulos
19 papers · 2019–2025 · 5 conferences · across top CS/AI conferences
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Conferences
NIPS (7)
ICML (6)
ICLR (4)
COLT (1)
JMLR (1)
Top co-authors
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