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Deep RL

3,861 papers

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Papers

Visual Tracking via Hierarchical Deep Reinforcement Learning AAAI 2021
Deep Reinforcement Learning at the Edge of the Statistical Precipice NIPS 2021
Robust Domain Randomised Reinforcement Learning through Peer-to-Peer Distillation ACML 2021
Towards Tight Bounds on the Sample Complexity of Average-reward MDPs ICML 2021
Objective-aware Traffic Simulation via Inverse Reinforcement Learning IJCAI 2021
Automatically Exposing Problems with Neural Dialog Models EMNLP 2021
Variable Frame Rate Acoustic Models Using Minimum Error Reinforcement Learning INTERSPEECH 2021
Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective COLT 2021
Monte Carlo Tree Search With Iteratively Refining State Abstractions NIPS 2021
Adversarial Intrinsic Motivation for Reinforcement Learning NIPS 2021
Continuous-time Model-based Reinforcement Learning ICML 2021
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation AAAI 2021
Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions IJCAI 2021
Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees ICML 2021
Dynamic Balancing for Model Selection in Bandits and RL ICML 2021
Reinforced Counterfactual Data Augmentation for Dual Sentiment Classification EMNLP 2021
Model-Based Episodic Memory Induces Dynamic Hybrid Controls NIPS 2021
ER-AE: Differentially Private Text Generation for Authorship Anonymization NAACL 2021
Unsupervised Domain Adaptation with Dynamics-Aware Rewards in Reinforcement Learning NIPS 2021
Variational Bayesian Reinforcement Learning with Regret Bounds NIPS 2021
Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning NIPS 2021
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations NIPS 2021
How RL Agents Behave When Their Actions Are Modified AAAI 2021
Learning Collaborative Policies to Solve NP-hard Routing Problems NIPS 2021
Emphatic Algorithms for Deep Reinforcement Learning ICML 2021