research
∙
06/24/2021
Task-agnostic Continual Learning with Hybrid Probabilistic Models
Learning new tasks continuously without forgetting on a constantly chang...
share
research
∙
12/09/2020
Neural Rate Control for Video Encoding using Imitation Learning
In modern video encoders, rate control is a critical component and has b...
research
∙
10/13/2020
Balancing Constraints and Rewards with Meta-Gradient D4PG
Deploying Reinforcement Learning (RL) agents to solve real-world applica...
research
∙
06/17/2020
A maximum-entropy approach to off-policy evaluation in average-reward MDPs
This work focuses on off-policy evaluation (OPE) with function approxima...
research
∙
03/24/2020
An empirical investigation of the challenges of real-world reinforcement learning
Reinforcement learning (RL) has proven its worth in a series of artifici...
research
∙
09/04/2019
Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control
Many real-world sequential decision-making problems can be formulated as...
research
∙
06/18/2019
Robust Reinforcement Learning for Continuous Control with Model Misspecification
We provide a framework for incorporating robustness -- to perturbations ...
research
∙
05/21/2017
Shallow Updates for Deep Reinforcement Learning
Deep reinforcement learning (DRL) methods such as the Deep Q-Network (DQ...
research
∙
02/23/2017
Rotting Bandits
The Multi-Armed Bandits (MAB) framework highlights the tension between a...
research
∙
04/16/2015