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Author

M. Kojima

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Preprint Sep 2026

Feedback-Aware Tuning of Recursive Q-Learning

Model choice in backward Q-learning is recursive because a later-stage choice changes the response supplied to an earlier regression and can alter its model-comparison statistic. Separate stagewise criteria do not directly assess the target-stage prediction risk of a completed Q-learning fit. We address this mismatch b...

M. Kojima · 0 citations
Preprint Aug 2026

Fast Power Evaluation under Biased-Coin Minimization: Sampling and Randomization Calibration

Design-stage power and sample-size evaluation under biased-coin minimization can be computationally intensive when a prespecified randomization test is reproduced within every simulated trial. We develop a reusable stratum-imbalance Gaussian approximation (SIGA) framework by exactly decomposing a fixed-score statistic...

M. Kojima · 0 citations

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