1 citations · 1 across the 2 of their papers we have counts for
2 papers
math.OC2023
Parameter-Agnostic Optimization under Relaxed Smoothness
Florian Hübler, Junchi Yang, Xiang Li +1
Tuning hyperparameters, such as the stepsize, presents a major challenge of training machine learning models. To address this challenge, numerous adaptive optimization algorithms h…
math.OC2023★ 1 cited
Two Sides of One Coin: the Limits of Untuned SGD and the Power of Adaptive Methods
Junchi Yang, Xiang Li, Ilyas Fatkhullin +1
The classical analysis of Stochastic Gradient Descent (SGD) with polynomially decaying stepsize relies on well-tuned depending on problem parameters such as…