Frank Proske — accepted AI-conference papers

2026

On the Interaction of Batch Noise, Adaptivity, and Compression, under $(L_0,L_1)$-Smoothness: An SDE Approach

Enea Monzio Compagnoni, Rustem Islamov, Frank Proske, Aurelien Lucchi, Antonio Orvieto, Eduard Gorbunov

ICML 2026poster

Distributed stochastic optimization intertwines (i) stochastic gradient noise, (ii) communication compression, and (iii) adaptive/normalized updates. While each factor has been studied in isolation, their joint effect under realistic assumptions remains poorly understood. In this work, we develop a …

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2024

SDEs for Minimax Optimization

Enea Monzio Compagnoni, Antonio Orvieto, Hans Kersting, Frank Proske, Aurelien Lucchi

AISTATS 2024poster

Minimax optimization problems have attracted a lot of attention over the past few years, with applications ranging from economics to machine learning. While advanced optimization methods exist for such problems, characterizing their dynamics in stochastic scenarios remains notably challenging. In th…

Cited by 4 Source ↗PDF ↗code ↗Scholar ↗

2022

Anticorrelated Noise Injection for Improved Generalization

Antonio Orvieto, Hans Kersting, Frank Proske, Francis Bach, Aurelien Lucchi

ICML 2022spotlight

Injecting artificial noise into gradient descent (GD) is commonly employed to improve the performance of machine learning models. Usually, uncorrelated noise is used in such perturbed gradient descent (PGD) methods. It is, however, not known if this is optimal or whether other types of noise could p…

Cited by 55 Source ↗PDF ↗Scholar ↗

2022

On the Theoretical Properties of Noise Correlation in Stochastic Optimization

Aurelien Lucchi, Frank Proske, Antonio Orvieto, Francis Bach, Hans Kersting

NeurIPS 2022accept

Studying the properties of stochastic noise to optimize complex non-convex functions has been an active area of research in the field of machine learning. Prior work~\citep{zhou2019pgd, wei2019noise} has shown that the noise of stochastic gradient descent improves optimization by overcoming undesira…

Cited by 9 Source ↗PDF ↗Scholar ↗