2 papers
stat.ML2025
Fast Escape, Slow Convergence: Learning Dynamics of Phase Retrieval under Power-Law Data
Guillaume Braun, Bruno Loureiro, Ha Quang Minh +1
Scaling laws describe how learning performance improves with data, compute, or training time, and have become a central theme in modern deep learning. We study this phenomenon in a…
stat.ML2025
Kernel ridge regression under power-law data: spectrum and generalization
Arie Wortsman, Bruno Loureiro
In this work, we investigate high-dimensional kernel ridge regression (KRR) on i.i.d. Gaussian data with anisotropic power-law covariance. This setting differs fundamentally from t…