4 citations · 7 across the 4 of their papers we have counts for
4 papers
Tune As You Scale: Hyperparameter Optimization For Compute Efficient Training
Abraham J. Fetterman, Ellie Kitanidis, Joshua Albrecht +6
Hyperparameter tuning of deep learning models can lead to order-of-magnitude performance gains for the same amount of compute. Despite this, systematic tuning is uncommon, particul…
Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds
Joshua Albrecht, Abraham J. Fetterman, Bryden Fogelman +8
Despite impressive successes, deep reinforcement learning (RL) systems still fall short of human performance on generalization to new tasks and environments that differ from their…
FusedProp: Towards Efficient Training of Generative Adversarial Networks
Zachary Polizzi, Chuan-Yung Tsai
Generative adversarial networks (GANs) are capable of generating strikingly realistic samples but state-of-the-art GANs can be extremely computationally expensive to train. In this…
A Networks and Machine Learning Approach to Determine the Best College Coaches of the 20th-21st Centuries
Tian-Shun Jiang, Zachary Polizzi, Christopher Yuan
Our objective is to find the five best college sports coaches of past century for three different sports. We decided to look at men's basketball, football, and baseball. We wanted…