research
∙
12/02/2022
An Information-Theoretic Analysis of Compute-Optimal Neural Scaling Laws
We study the compute-optimal trade-off between model and training data s...
share
research
∙
09/18/2022
Is Stochastic Gradient Descent Near Optimal?
The success of neural networks over the past decade has established them...
research
∙
03/01/2022
Sample Complexity versus Depth: An Information Theoretic Analysis
Deep learning has proven effective across a range of data sets. In light...
research
∙
07/06/2021
Learning Latent Actions to Control Assistive Robots
Assistive robot arms enable people with disabilities to conduct everyday...
research
∙
05/07/2020
Shared Autonomy with Learned Latent Actions
Assistive robots enable people with disabilities to conduct everyday tas...
research
∙
02/12/2020
Reward-rational (implicit) choice: A unifying formalism for reward learning
It is often difficult to hand-specify what the correct reward function i...
research
∙
08/12/2018
