Adaptive Accelerated Gradient Method for Smooth Convex Optimization

This article likely presents a new algorithm or improvement to an existing algorithm for solving optimization problems. The focus is on smooth convex optimization, a common problem in machine learning and other fields. The term "adaptive" suggests the method adjusts its parameters during the optimization process, and "accelerated" implies it aims for faster convergence compared to standard gradient descent.