Zhongwen Xu | DeepAI

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∙ 02/03/2023

Learning to Optimize for Reinforcement Learning

In recent years, by leveraging more data, computation, and diverse tasks...

0 Qingfeng Lan, et al. ∙

∙ 02/02/2023

Visual Imitation Learning with Patch Rewards

Visual imitation learning enables reinforcement learning agents to learn...

0 Minghuan Liu, et al. ∙

∙ 01/27/2023

Reinforcement Learning from Diverse Human Preferences

The complexity of designing reward functions has been a major obstacle t...

0 Wanqi Xue, et al. ∙

∙ 10/24/2022

Benchmarking Deformable Object Manipulation with Differentiable Physics

Deformable Object Manipulation (DOM) is of significant importance to bot...

0 Siwei Chen, et al. ∙

∙ 10/18/2022

RPM: Generalizable Behaviors for Multi-Agent Reinforcement Learning

Despite the recent advancement in multi-agent reinforcement learning (MA...

5 Wei Qiu, et al. ∙

∙ 10/17/2022

Boosting Offline Reinforcement Learning via Data Rebalancing

Offline reinforcement learning (RL) is challenged by the distributional ...

5 Yang Yue, et al. ∙

∙ 10/14/2022

Mutual Information Regularized Offline Reinforcement Learning

Offline reinforcement learning (RL) aims at learning an effective policy...

6 Xiao Ma, et al. ∙

∙ 10/12/2022

Efficient Offline Policy Optimization with a Learned Model

MuZero Unplugged presents a promising approach for offline policy learni...

0 Zichen Liu, et al. ∙

∙ 06/25/2022

Value-Consistent Representation Learning for Data-Efficient Reinforcement Learning

Deep reinforcement learning (RL) algorithms suffer severe performance de...

6 Yang Yue, et al. ∙

∙ 06/21/2022

EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine

There has been significant progress in developing reinforcement learning...

8 Jiayi Weng, et al. ∙

∙ 06/10/2022

Imitation Learning via Differentiable Physics

Existing imitation learning (IL) methods such as inverse reinforcement l...

8 Siwei Chen, et al. ∙

∙ 08/25/2021

ETA Prediction with Graph Neural Networks in Google Maps

Travel-time prediction constitutes a task of high importance in transpor...

13 Austin Derrow-Pinion, et al. ∙

∙ 06/21/2021

Emphatic Algorithms for Deep Reinforcement Learning

Off-policy learning allows us to learn about possible policies of behavi...

0 Ray Jiang, et al. ∙

∙ 02/12/2021

Discovery of Options via Meta-Learned Subgoals

Temporal abstractions in the form of options have been shown to help rei...

5 Vivek Veeriah, et al. ∙

∙ 10/13/2020

Balancing Constraints and Rewards with Meta-Gradient D4PG

Deploying Reinforcement Learning (RL) agents to solve real-world applica...

0 Dan A. Calian, et al. ∙

∙ 07/17/2020

Discovering Reinforcement Learning Algorithms

Reinforcement learning (RL) algorithms update an agent's parameters acco...

72 Junhyuk Oh, et al. ∙

∙ 07/16/2020

Meta-Gradient Reinforcement Learning with an Objective Discovered Online

Deep reinforcement learning includes a broad family of algorithms that p...

9 Zhongwen Xu, et al. ∙

∙ 02/28/2020

Self-Tuning Deep Reinforcement Learning

Reinforcement learning (RL) algorithms often require expensive manual or...

20 Tom Zahavy, et al. ∙

∙ 12/11/2019

What Can Learned Intrinsic Rewards Capture?

Reinforcement learning agents can include different components, such as ...

25 Zeyu Zheng, et al. ∙

∙ 09/10/2019

Discovery of Useful Questions as Auxiliary Tasks

Arguably, intelligent agents ought to be able to discover their own ques...

7 Vivek Veeriah, et al. ∙

∙ 07/08/2019

General non-linear Bellman equations

We consider a general class of non-linear Bellman equations. These open ...

5 Hado van Hasselt, et al. ∙

∙ 05/24/2018

Meta-Gradient Reinforcement Learning

The goal of reinforcement learning algorithms is to estimate and/or opti...

0 Zhongwen Xu, et al. ∙

∙ 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...

0 Fan Wu, et al. ∙

∙ 12/19/2016

Few-Shot Object Recognition from Machine-Labeled Web Images

With the tremendous advances of Convolutional Neural Networks (ConvNets)...

0 Zhongwen Xu, et al. ∙

∙ 11/28/2016

Bidirectional Multirate Reconstruction for Temporal Modeling in Videos

Despite the recent success of neural networks in image feature learning,...

0 Linchao Zhu, et al. ∙

∙ 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...

0 Shoou-I Yu, et al. ∙

∙ 11/11/2015

Hierarchical Recurrent Neural Encoder for Video Representation with Application to Captioning

Recently, deep learning approach, especially deep Convolutional Neural N...

0 Pingbo Pan, et al. ∙

∙ 11/14/2014

A Discriminative CNN Video Representation for Event Detection

In this paper, we propose a discriminative video representation for even...

0 Zhongwen Xu, et al. ∙

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