research
∙
02/12/2023
Policy-Induced Self-Supervision Improves Representation Finetuning in Visual RL
We study how to transfer representations pretrained on source tasks to t...
share
research
∙
01/18/2023
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Despite the advancement of machine learning techniques in recent years, ...
research
∙
02/16/2022
Policy Learning and Evaluation with Randomized Quasi-Monte Carlo
Reinforcement learning constantly deals with hard integrals, for example...
research
∙
08/03/2021
Uniform Sampling over Episode Difficulty
Episodic training is a core ingredient of few-shot learning to train mod...
research
∙
04/15/2021
Embedding Adaptation is Still Needed for Few-Shot Learning
Constructing new and more challenging tasksets is a fruitful methodology...
research
∙
08/27/2020
learn2learn: A Library for Meta-Learning Research
Meta-learning researchers face two fundamental issues in their empirical...
research
∙
10/30/2019
Decoupling Adaptation from Modeling with Meta-Optimizers for Meta Learning
Meta-learning methods, most notably Model-Agnostic Meta-Learning or MAML...
research
∙
10/02/2019
Analyzing the Variance of Policy Gradient Estimators for the Linear-Quadratic Regulator
We study the variance of the REINFORCE policy gradient estimator in envi...
research
∙
06/08/2019
