Policy Learning and Evaluation with Randomized Quasi-Monte Carlo
Poster for our work on reducing the variance with RQMC in reinforcement learning.
AISTATS, 2022
[pdf]
Uniform Sampling Over Episode Difficulty
Poster for our work on sampling episodes in few-shot learning.
NeurIPS, 2021
[pdf]
When MAML Can Adapt Fast and How to Assist When it Cannot
Poster for our work on helping MAML learn to adapt.
AISTATS, 2021
[pdf]
Reducing the variance in online optimization by transporting past gradients
Poster for our work on implicit gradient transport.
NeurIPS, 2019
[pdf]
cherry: A Reinforcement Learning Framework for Researchers
An overview of cherry.
PyTorch Dev Conference, 2019
[pdf]
learn2learn: A Meta-Learning Framework for Researchers
An overview of learn2learn.
PyTorch Dev Conference, 2019
[pdf]
Managing Machine Learning Experiments
How to use randopt to manage machine learning experiments.
PyCon, 2018
[pdf]
Accelerating SGD for Distributed Deep Learning Using Approximated Hessian Matrix
Approximating the Hessian via finite differences in the distributed setting.
ICLR Workshop, 2017
[pdf]