126 citations · 136 across the 7 of their papers we have counts for
3 papers · 1 filter
How far away are truly hyperparameter-free learning algorithms?
Priya Kasimbeg, Vincent Roulet, Naman Agarwal +4
Despite major advances in methodology, hyperparameter tuning remains a crucial (and expensive) part of the development of machine learning systems. Even ignoring architectural choi…
Training neural networks faster with minimal tuning using pre-computed lists of hyperparameters for NAdamW
Sourabh Medapati, Priya Kasimbeg, Shankar Krishnan +2
If we want to train a neural network using any of the most popular optimization algorithms, we are immediately faced with a dilemma: how to set the various optimization and regular…
Accelerating Neural Network Training: An Analysis of the AlgoPerf Competition
Priya Kasimbeg, Frank Schneider, Runa Eschenhagen +11
The goal of the AlgoPerf: Training Algorithms competition is to evaluate practical speed-ups in neural network training achieved solely by improving the underlying training algorit…