Kimon Antonakopoulos

papers

132

total citations

papers (12)

On the Generalization of Stochastic Gradient Descent with Momentum

ICML 2024arXiv

citations

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

NEURIPS 2022arXiv

citations

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization

NEURIPS 2022arXiv

citations

Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods

NEURIPS 2022arXiv

citations

Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness

ICLR 2024arXiv

citations

Fast Routing under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights

NEURIPS 2021

citations

Adaptive First-Order Methods Revisited: Convex Minimization without Lipschitz Requirements

NEURIPS 2021

citations

Sifting through the noise: Universal first-order methods for stochastic variational inequalities

NEURIPS 2021

citations

Kimon Antonakopoulos

papers (12)

On the Generalization of Stochastic Gradient Descent with Momentum

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization

Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods

Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness

Universal Gradient Methods for Stochastic Convex Optimization

Generalized Gradient Norm Clipping & Non-Euclidean $(L_0,L_1)$-Smoothness

Improving SAM Requires Rethinking its Optimization Formulation

Layer-wise Quantization for Quantized Optimistic Dual Averaging

Fast Routing under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights

Adaptive First-Order Methods Revisited: Convex Minimization without Lipschitz Requirements

Sifting through the noise: Universal first-order methods for stochastic variational inequalities

papers (12)

On the Generalization of Stochastic Gradient Descent with Momentum

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization

Extra-Newton: A First Approach to Noise-Adaptive Accelerated Second-Order Methods

Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness

Universal Gradient Methods for Stochastic Convex Optimization

Generalized Gradient Norm Clipping & Non-Euclidean $(L_0,L_1)$-Smoothness

Improving SAM Requires Rethinking its Optimization Formulation

Layer-wise Quantization for Quantized Optimistic Dual Averaging

Fast Routing under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights

Adaptive First-Order Methods Revisited: Convex Minimization without Lipschitz Requirements

Sifting through the noise: Universal first-order methods for stochastic variational inequalities