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Deep RL

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Papers

A data-driven approach for learning to control computers ICML 2022
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation ICML 2022
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling ICML 2022
Large Batch Experience Replay ICML 2022
Goal Misgeneralization in Deep Reinforcement Learning ICML 2022
Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field Regime ICML 2022
Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning ICML 2022
Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks ICML 2022
Delayed Reinforcement Learning by Imitation ICML 2022
Distributionally Robust $Q$-Learning ICML 2022
How to Stay Curious while avoiding Noisy TVs using Aleatoric Uncertainty Estimation ICML 2022
Optimizing Tensor Network Contraction Using Reinforcement Learning ICML 2022
Transformers are Meta-Reinforcement Learners ICML 2022
Learning Stochastic Shortest Path with Linear Function Approximation ICML 2022
A Simple Reward-free Approach to Constrained Reinforcement Learning ICML 2022
EqR: Equivariant Representations for Data-Efficient Reinforcement Learning ICML 2022
CtrlFormer: Learning Transferable State Representation for Visual Control via Transformer ICML 2022
The Primacy Bias in Deep Reinforcement Learning ICML 2022
History Compression via Language Models in Reinforcement Learning ICML 2022
Evolving Curricula with Regret-Based Environment Design ICML 2022
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution ICML 2022
Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost ICML 2022
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning ICML 2022
Direct Behavior Specification via Constrained Reinforcement Learning ICML 2022
Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity ICML 2022