Francesco Orabona

Better Parameter-free Stochastic Optimization with ODE Updates for Coin-Betting

2020 · arXiv (Cornell University)

Parameter-free stochastic gradient descent (PFSGD) algorithms do not require setting learning rates while achieving optimal theoretical performance. In practical applications, however, there remains an empirical gap between tuned stochastic gradient descent (SGD) and PFSGD. In …