Theoretical Analysis of Sparse Optimization with Reparameterization, Weight Decay, and Adaptive Learning Rate

Abstract

Sparse optimization is a fundamental challenge in various practical applications. A popular approach to sparse optimization is Lp regularization. However, it may encounter optimization instability due to the unbounded gradients when 0