8月28日
研討會, 演講, 講座
MATH - Seminar on Statistics and Machine Learning - ROOT-SGD: Sharp Nonasymptotics and Asymptotic Efficiency in a Single Algorithm
The theory and practice of stochastic optimization has focused on stochastic gradient descent (SGD) in recent years, retaining the basic first-order stochastic nature of SGD while aiming to improve it via mechanisms such as averaging, momentum, and variance reduction.