research
∙
06/30/2022
Watch and Match: Supercharging Imitation with Regularized Optimal Transport
Imitation learning holds tremendous promise in learning policies efficie...
share
research
∙
02/01/2022
CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery
We introduce Contrastive Intrinsic Control (CIC), an algorithm for unsup...
research
∙
01/31/2022
Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning
Recent progress in deep learning has relied on access to large and diver...
research
∙
10/28/2021
URLB: Unsupervised Reinforcement Learning Benchmark
Deep Reinforcement Learning (RL) has emerged as a powerful paradigm to s...
research
∙
07/20/2021
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
We present DrQ-v2, a model-free reinforcement learning (RL) algorithm fo...
research
∙
02/22/2021
Reinforcement Learning with Prototypical Representations
Learning effective representations in image-based environments is crucia...
research
∙
11/24/2020
Learning Navigation Skills for Legged Robots with Learned Robot Embeddings
Navigation policies are commonly learned on idealized cylinder agents in...
research
∙
08/28/2020
On the model-based stochastic value gradient for continuous reinforcement learning
Model-based reinforcement learning approaches add explicit domain knowle...
research
∙
06/23/2020
Automatic Data Augmentation for Generalization in Deep Reinforcement Learning
Deep reinforcement learning (RL) agents often fail to generalize to unse...
research
∙
04/28/2020
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
We propose a simple data augmentation technique that can be applied to s...
research
∙
10/09/2019
On the adequacy of untuned warmup for adaptive optimization
Adaptive optimization algorithms such as Adam (Kingma Ba, 2014) are ...
research
∙
10/03/2019
Generalized Inner Loop Meta-Learning
Many (but not all) approaches self-qualifying as "meta-learning" in deep...
research
∙
10/02/2019
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images
Training an agent to solve control tasks directly from high-dimensional ...
research
∙
09/27/2019
The Differentiable Cross-Entropy Method
We study the Cross-Entropy Method (CEM) for the non-convex optimization ...
research
∙
06/03/2019
Hierarchical Decision Making by Generating and Following Natural Language Instructions
We explore using latent natural language instructions as an expressive a...
research
∙
10/16/2018
Quasi-hyperbolic momentum and Adam for deep learning
Momentum-based acceleration of stochastic gradient descent (SGD) is wide...
research
∙
12/15/2017
Hierarchical Text Generation and Planning for Strategic Dialogue
End-to-end models for strategic dialogue are challenging to train, becau...
research
∙
06/16/2017
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
Much of human dialogue occurs in semi-cooperative settings, where agents...
research
∙
05/08/2017