55 citations · 61 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…
On the Stepwise Nature of Self-Supervised Learning
James B. Simon, Maksis Knutins, Liu Ziyin +3
We present a simple picture of the training process of joint embedding self-supervised learning methods. We find that these methods learn their high-dimensional embeddings one dime…
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…
Large Transport Gap Modulation in Graphene via Electric Field Controlled Reversible Hydrogenation
Shaorui Li, Jiaheng Li, Yongchao Wang +5
Graphene is of interest in the development of next-generation electronics due to its high electron mobility, flexibility and stability. However, graphene transistors have poor on/o…