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20182023
most citedA Review of Safe Reinforcement Learning: Methods, Theory and Applications

102 citations · 255 across the 30 of their papers we have counts for

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Showing 2022Show all

9 papers · 1 filter

cs.CV2022★ 17 cited

Multi-queue Momentum Contrast for Microvideo-Product Retrieval

Yali Du, Yinwei Wei, Wei Ji +3

The booming development and huge market of micro-videos bring new e-commerce channels for merchants. Currently, more micro-video publishers prefer to embed relevant ads into their…

cs.LG2022★ 4 cited

Contextual Transformer for Offline Meta Reinforcement Learning

Runji Lin, Ye Li, Xidong Feng +6

The pretrain-finetuning paradigm in large-scale sequence models has made significant progress in natural language processing and computer vision tasks. However, such a paradigm is…

cs.CV2022★ 2 cited

Interpretable Dimensionality Reduction by Feature Preserving Manifold Approximation and Projection

Yang Yang, Hongjian Sun, Jialei Gong +1

Nonlinear dimensionality reduction lacks interpretability due to the absence of source features in low-dimensional embedding space. We propose an interpretable method featMAP to pr…

cs.LG2022★ 1 cited

Scalable Model-based Policy Optimization for Decentralized Networked Systems

Yali Du, Chengdong Ma, Yuchen Liu +4

Reinforcement learning algorithms require a large amount of samples; this often limits their real-world applications on even simple tasks. Such a challenge is more outstanding in m…

cs.AI2022★ 102 cited

A Review of Safe Reinforcement Learning: Methods, Theory and Applications

Shangding Gu, Long Yang, Yali Du +4

Reinforcement Learning (RL) has achieved tremendous success in many complex decision-making tasks. However, safety concerns are raised during deploying RL in real-world application…

cs.CL2022

Perceiving the World: Question-guided Reinforcement Learning for Text-based Games

Yunqiu Xu, Meng Fang, Ling Chen +3

Text-based games provide an interactive way to study natural language processing. While deep reinforcement learning has shown effectiveness in developing the game playing agent, th…

cs.LG2022★ 13 cited

Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL

Rui Yang, Yiming Lu, Wenzhe Li +6

Solving goal-conditioned tasks with sparse rewards using self-supervised learning is promising because of its simplicity and stability over current reinforcement learning (RL) algo…

cs.LG2022

Learning to Identify Top Elo Ratings: A Dueling Bandits Approach

Xue Yan, Yali Du, Binxin Ru +3

The Elo rating system is widely adopted to evaluate the skills of (chess) game and sports players. Recently it has been also integrated into machine learning algorithms in evaluati…

cs.MA2022★ 25 cited

GCS: Graph-based Coordination Strategy for Multi-Agent Reinforcement Learning

Jingqing Ruan, Yali Du, Xuantang Xiong +6

Many real-world scenarios involve a team of agents that have to coordinate their policies to achieve a shared goal. Previous studies mainly focus on decentralized control to maximi…