4 papers
Online Bootstrap Inference for the Trend of Nonstationary Time Series
Thomas Nagler, Tobias Brock, Nicolai Palm
This article proposes an online bootstrap scheme for nonparametric level estimation in nonstationary time series. Our approach applies to a broad class of level estimators expressi…
Uniform central limit theorems for non-stationary processes via relative weak convergence
Nicolai Palm, Thomas Nagler
Statistical inference for non-stationary data is hindered by the failure of classical central limit theorems (CLTs), not least because there is no fixed Gaussian limit to converge…
Paths and Ambient Spaces in Neural Loss Landscapes
Daniel Dold, Julius Kobialka, Nicolai Palm +3
Understanding the structure of neural network loss surfaces, particularly the emergence of low-loss tunnels, is critical for advancing neural network theory and practice. In this p…
An Online Bootstrap for Time Series
Nicolai Palm, Thomas Nagler
Resampling methods such as the bootstrap have proven invaluable in the field of machine learning. However, the applicability of traditional bootstrap methods is limited when dealin…