research
∙
08/17/2023
Reinforced Self-Training (ReST) for Language Modeling
Reinforcement learning from human feedback (RLHF) can improve the qualit...
share
research
∙
06/16/2023
π2vec: Policy Representations with Successor Features
This paper describes π2vec, a method for representing behaviors of black...
research
∙
03/13/2023
Vision-Language Models as Success Detectors
Detecting successful behaviour is crucial for training intelligent agent...
research
∙
02/17/2022
Retrieval-Augmented Reinforcement Learning
Most deep reinforcement learning (RL) algorithms distill experience into...
research
∙
06/18/2021
Active Offline Policy Selection
This paper addresses the problem of policy selection in domains with abu...
research
∙
12/12/2020
Semi-supervised reward learning for offline reinforcement learning
In offline reinforcement learning (RL) agents are trained using a logged...
research
∙
11/27/2020
Offline Learning from Demonstrations and Unlabeled Experience
Behavior cloning (BC) is often practical for robot learning because it a...
research
∙
09/26/2019
A Framework for Data-Driven Robotics
We present a framework for data-driven robotics that makes use of a larg...
research
∙
10/09/2018
Discovering General-Purpose Active Learning Strategies
We propose a general-purpose approach to discovering active learning (AL...
research
∙
12/21/2017
Learning Intelligent Dialogs for Bounding Box Annotation
We introduce Intelligent Annotation Dialogs for bounding box annotation....
research
∙
06/29/2016
Geometry in Active Learning for Binary and Multi-class Image Segmentation
We propose an Active Learning approach to image segmentation that exploi...
research
∙
11/11/2015