Asymptotic Risk of Learning-Rate Schedules for Least-Squares Regression with Discretely Distributed Features
We study the last iterate of stochastic gradient descent (SGD) on streaming least squares with discretely distributed features (Slock's model), which decouples the dynamics across eigendirections. Under power-law source and capacity conditions, we derive the exact finite-time risk and asymptotic equivalents of constant...