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02/03/2023
Learning to Optimize for Reinforcement Learning
In recent years, by leveraging more data, computation, and diverse tasks...
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02/02/2023
Visual Imitation Learning with Patch Rewards
Visual imitation learning enables reinforcement learning agents to learn...
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01/27/2023
Reinforcement Learning from Diverse Human Preferences
The complexity of designing reward functions has been a major obstacle t...
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10/24/2022
Benchmarking Deformable Object Manipulation with Differentiable Physics
Deformable Object Manipulation (DOM) is of significant importance to bot...
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10/18/2022
RPM: Generalizable Behaviors for Multi-Agent Reinforcement Learning
Despite the recent advancement in multi-agent reinforcement learning (MA...
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10/17/2022
Boosting Offline Reinforcement Learning via Data Rebalancing
Offline reinforcement learning (RL) is challenged by the distributional ...
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10/14/2022
Mutual Information Regularized Offline Reinforcement Learning
Offline reinforcement learning (RL) aims at learning an effective policy...
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10/12/2022
Efficient Offline Policy Optimization with a Learned Model
MuZero Unplugged presents a promising approach for offline policy learni...
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06/25/2022
Value-Consistent Representation Learning for Data-Efficient Reinforcement Learning
Deep reinforcement learning (RL) algorithms suffer severe performance de...
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06/21/2022
EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine
There has been significant progress in developing reinforcement learning...
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06/10/2022
Imitation Learning via Differentiable Physics
Existing imitation learning (IL) methods such as inverse reinforcement l...
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08/25/2021
ETA Prediction with Graph Neural Networks in Google Maps
Travel-time prediction constitutes a task of high importance in transpor...
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06/21/2021
Emphatic Algorithms for Deep Reinforcement Learning
Off-policy learning allows us to learn about possible policies of behavi...
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02/12/2021
Discovery of Options via Meta-Learned Subgoals
Temporal abstractions in the form of options have been shown to help rei...
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10/13/2020
Balancing Constraints and Rewards with Meta-Gradient D4PG
Deploying Reinforcement Learning (RL) agents to solve real-world applica...
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07/17/2020
Discovering Reinforcement Learning Algorithms
Reinforcement learning (RL) algorithms update an agent's parameters acco...
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07/16/2020
Meta-Gradient Reinforcement Learning with an Objective Discovered Online
Deep reinforcement learning includes a broad family of algorithms that p...
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02/28/2020
Self-Tuning Deep Reinforcement Learning
Reinforcement learning (RL) algorithms often require expensive manual or...
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12/11/2019
What Can Learned Intrinsic Rewards Capture?
Reinforcement learning agents can include different components, such as ...
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09/10/2019
Discovery of Useful Questions as Auxiliary Tasks
Arguably, intelligent agents ought to be able to discover their own ques...
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07/08/2019
General non-linear Bellman equations
We consider a general class of non-linear Bellman equations. These open ...
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05/24/2018
Meta-Gradient Reinforcement Learning
The goal of reinforcement learning algorithms is to estimate and/or opti...
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03/22/2017
An End-to-End Approach to Natural Language Object Retrieval via Context-Aware Deep Reinforcement Learning
We propose an end-to-end approach to the natural language object retriev...
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12/19/2016
Few-Shot Object Recognition from Machine-Labeled Web Images
With the tremendous advances of Convolutional Neural Networks (ConvNets)...
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11/28/2016
Bidirectional Multirate Reconstruction for Temporal Modeling in Videos
Despite the recent success of neural networks in image feature learning,...
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06/17/2016
Strategies for Searching Video Content with Text Queries or Video Examples
The large number of user-generated videos uploaded on to the Internet ev...
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11/11/2015
Hierarchical Recurrent Neural Encoder for Video Representation with Application to Captioning
Recently, deep learning approach, especially deep Convolutional Neural N...
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11/14/2014