sample efficiency

469 papers

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Co-occurring keywords

reinforcement learning (4122) deep reinforcement learning (903) model-based reinforcement learning (415) representation learning (6174) policy gradient (518) policy optimization (630) continuous control (246) off-policy learning (227) value function (294) imitation learning (741)

Papers

Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing ICML 2023

Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck NIPS 2023

Provably Efficient Algorithm for Nonstationary Low-Rank MDPs NIPS 2023

Look Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL NIPS 2023

Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning NIPS 2023

EfficientOCR: An Extensible, Open-Source Package for Efficiently Digitizing World Knowledge EMNLP 2023

Sample Efficiency of Data Augmentation Consistency Regularization AISTATS 2023

Flatness-Aware Prompt Selection Improves Accuracy and Sample Efficiency EMNLP 2023

Let’s Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs EMNLP 2023

Are Sample-Efficient NLP Models More Robust? ACL 2023

An Investigation into Pre-Training Object-Centric Representations for Reinforcement Learning ICML 2023

The Distributional Hypothesis Does Not Fully Explain the Benefits of Masked Language Model Pretraining EMNLP 2023

On Many-Actions Policy Gradient ICML 2023

Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation ICML 2023

Improving Adversarial Robustness Through the Contrastive-Guided Diffusion Process ICML 2023

Adaptive Policy Learning for Offline-to-Online Reinforcement Learning AAAI 2023

VA-learning as a more efficient alternative to Q-learning ICML 2023

On Sample-Efficient Offline Reinforcement Learning: Data Diversity, Posterior Sampling and Beyond NIPS 2023

Bigger, Better, Faster: Human-level Atari with human-level efficiency ICML 2023

Provable Hierarchy-Based Meta-Reinforcement Learning AISTATS 2023

Multiple-policy High-confidence Policy Evaluation AISTATS 2023

FedSysID: A Federated Approach to Sample-Efficient System Identification L4DC 2023

Multi-Task Imitation Learning for Linear Dynamical Systems L4DC 2023

No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities AISTATS 2023

Metric Residual Network for Sample Efficient Goal-Conditioned Reinforcement Learning AAAI 2023