arXiv stat.ML
· Papers
Langevin dynamics for high-dimensional optimization: the case of multi-spiked tensor PCA
arXiv:2408.06401v3 Announce Type: replace Abstract: We study nonconvex optimization in high dimensions through Langevin dynamics, focusing on the multi-spiked tensor PCA problem. In this tensor estimation model, the goal is to recover a finite number of hidden signal vectors, or spikes, from noisy Gaussian tensor obser