26 citations · 58 across the 10 of their papers we have counts for
4 papers · 1 filter
On the Theoretical Properties of Noise Correlation in Stochastic Optimization
Aurelien Lucchi, Frank Proske, Antonio Orvieto +2
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 has shown that…
Mean first exit times of Ornstein-Uhlenbeck processes in high-dimensional spaces
Hans Kersting, Antonio Orvieto, Frank Proske +1
The -dimensional Ornstein--Uhlenbeck process (OUP) describes the trajectory of a particle in a -dimensional, spherically symmetric, quadratic potential. The OUP is composed o…
Explicit Regularization in Overparametrized Models via Noise Injection
Antonio Orvieto, Anant Raj, Hans Kersting +1
Injecting noise within gradient descent has several desirable features, such as smoothing and regularizing properties. In this paper, we investigate the effects of injecting noise…
Anticorrelated Noise Injection for Improved Generalization
Antonio Orvieto, Hans Kersting, Frank Proske +2
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 pertur…