Kimon Antonakopoulos

According to our database1, Kimon Antonakopoulos authored at least 19 papers between 2019 and 2024.

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Bibliography

2024
On the Generalization of Stochastic Gradient Descent with Momentum.
J. Mach. Learn. Res., 2024

Improving SAM Requires Rethinking its Optimization Formulation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Universal Gradient Methods for Stochastic Convex Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Distributed Extra-gradient with Optimal Complexity and Communication Guarantees.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Routing in an Uncertain World: Adaptivity, Efficiency, and Equilibrium.
CoRR, 2022

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

UnderGrad: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees.
Proceedings of the International Conference on Machine Learning, 2022

AdaGrad Avoids Saddle Points.
Proceedings of the International Conference on Machine Learning, 2022

2021
Adaptive first-order methods revisited: Convex optimization without Lipschitz requirements.
CoRR, 2021

Fast Routing under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Sifting through the noise: Universal first-order methods for stochastic variational inequalities.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adaptive First-Order Methods Revisited: Convex Minimization without Lipschitz Requirements.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adaptive Extra-Gradient Methods for Min-Max Optimization and Games.
Proceedings of the 9th International Conference on Learning Representations, 2021

Adaptive Learning in Continuous Games: Optimal Regret Bounds and Convergence to Nash Equilibrium.
Proceedings of the Conference on Learning Theory, 2021

2020
Online and stochastic optimization beyond Lipschitz continuity: A Riemannian approach.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
An adaptive Mirror-Prox method for variational inequalities with singular operators.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019


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