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2 results for “sample complexity”
SPIN Processed News Frame: The Hype
The Sample Complexity of Policy Learning with Mu-Resets
A theoretical reinforcement learning paper establishes new exponential lower and upper bounds on sample complexity for policy learning under the μ-resets protocol, clarifying how horizon dependence scales with different concentrability assumptions.
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arXiv Machine Learning
Aug 11, 2026
SPIN Processed News Frame: The Hype
Hypergradient-based Bilevel Reinforcement Learning with Improved Sample Complexity
A new bilevel reinforcement learning algorithm is proposed that avoids Hessian computation and achieves improved sample complexity bounds compared to prior methods, advancing theoretical foundations for meta-learning and RL from human feedback.
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arXiv Machine Learning
Aug 3, 2026