2 papers
cs.LG2026
Information Hidden in Gradients of Regression with Target Noise
Arash Jamshidi, Katsiaryna Haitsiukevich, Kai Puolamäki
Second-order information -- such as curvature or data covariance -- is critical for optimisation, diagnostics, and robustness. However, in many modern settings, only the gradients…
cs.LG2025
GRADSTOP: Early Stopping of Gradient Descent via Posterior Sampling
Arash Jamshidi, Lauri Seppäläinen, Katsiaryna Haitsiukevich +3
Machine learning models are often learned by minimising a loss function on the training data using a gradient descent algorithm. These models often suffer from overfitting, leading…