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08/24/2023
Master-slave Deep Architecture for Top-K Multi-armed Bandits with Non-linear Bandit Feedback and Diversity Constraints
We propose a novel master-slave architecture to solve the top-K combinat...
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07/10/2023
RLTF: Reinforcement Learning from Unit Test Feedback
The goal of program synthesis, or code generation, is to generate execut...
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05/26/2023
Future-conditioned Unsupervised Pretraining for Decision Transformer
Recent research in offline reinforcement learning (RL) has demonstrated ...
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04/27/2023
SeeHow: Workflow Extraction from Programming Screencasts through Action-Aware Video Analytics
Programming screencasts (e.g., video tutorials on Youtube or live coding...
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03/13/2023
Deploying Offline Reinforcement Learning with Human Feedback
Reinforcement learning (RL) has shown promise for decision-making tasks ...
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02/05/2023
Sample Dropout: A Simple yet Effective Variance Reduction Technique in Deep Policy Optimization
Recent success in Deep Reinforcement Learning (DRL) methods has shown th...
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01/20/2023
Revisiting Estimation Bias in Policy Gradients for Deep Reinforcement Learning
We revisit the estimation bias in policy gradients for the discounted ep...
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12/04/2022
RLogist: Fast Observation Strategy on Whole-slide Images with Deep Reinforcement Learning
Whole-slide images (WSI) in computational pathology have high resolution...
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11/08/2022
Pretraining in Deep Reinforcement Learning: A Survey
The past few years have seen rapid progress in combining reinforcement l...
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11/07/2022
Curriculum-based Asymmetric Multi-task Reinforcement Learning
We introduce CAMRL, the first curriculum-based asymmetric multi-task lea...
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10/19/2022
Robust Offline Reinforcement Learning with Gradient Penalty and Constraint Relaxation
A promising paradigm for offline reinforcement learning (RL) is to const...
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09/26/2022
More Centralized Training, Still Decentralized Execution: Multi-Agent Conditional Policy Factorization
In cooperative multi-agent reinforcement learning (MARL), combining valu...
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09/21/2022
Revisiting Discrete Soft Actor-Critic
We study the adaption of soft actor-critic (SAC) from continuous action ...
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09/01/2022
Dynamics-Adaptive Continual Reinforcement Learning via Progressive Contextualization
A key challenge of continual reinforcement learning (CRL) in dynamic env...
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08/11/2022
Quantized Adaptive Subgradient Algorithms and Their Applications
Data explosion and an increase in model size drive the remarkable advanc...
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05/12/2022
GPN: A Joint Structural Learning Framework for Graph Neural Networks
Graph neural networks (GNNs) have been applied into a variety of graph t...
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02/17/2022
MineRL Diamond 2021 Competition: Overview, Results, and Lessons Learned
Reinforcement learning competitions advance the field by providing appro...
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12/07/2021
JueWu-MC: Playing Minecraft with Sample-efficient Hierarchical Reinforcement Learning
Learning rational behaviors in open-world games like Minecraft remains t...
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11/07/2021
Coordinated Proximal Policy Optimization
We present Coordinated Proximal Policy Optimization (CoPPO), an algorith...
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10/09/2021
TiKick: Toward Playing Multi-agent Football Full Games from Single-agent Demonstrations
Deep reinforcement learning (DRL) has achieved super-human performance o...
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06/19/2021
Boosting Offline Reinforcement Learning with Residual Generative Modeling
Offline reinforcement learning (RL) tries to learn the near-optimal poli...
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05/13/2021
MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks
In Goal-oriented Reinforcement learning, relabeling the raw goals in pas...
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01/05/2021
Generating Informative CVE Description From ExploitDB Posts by Extractive Summarization
ExploitDB is one of the important public websites, which contributes a l...
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12/18/2020
Which Heroes to Pick? Learning to Draft in MOBA Games with Neural Networks and Tree Search
Hero drafting is essential in MOBA game playing as it builds the team of...
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11/25/2020
Towards Playing Full MOBA Games with Deep Reinforcement Learning
MOBA games, e.g., Honor of Kings, League of Legends, and Dota 2, pose gr...
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11/25/2020
