Author

Ian Waudby-Smith

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Jul 2026

Gaffke's confidence interval for the mean of bounded data is inadmissible but asymptotically efficient

Given observations $\mathbf x=(x_1,\dots,x_n)$, Gaffke (2005) defined \[ K_n(\mathbf x)=\mathbb{P}_{\mathbf D}\!\left\{\sum_{i=1}^n x_iD_i\le 1\right\}, \qquad (D_0,D_1,\ldots,D_n)\sim\mathrm{Dirichlet}(1,\ldots,1), \] and conjectured that it is a $p$-value whenever the inputs are independent e-values. Recently, Vlassi...

Jiahao Ming, Aaditya Ramdas, Yi Shen et al. · arXiv.org · 4 citations · ⚡1

#machine learning Jul 2026

Post-Training at the Edge of Detectability: A Game-Theoretic Approach to Fine-Tuning

This work proposes a game-theoretic framework that gives this reward-retention trade-off an explicit statistical interpretation, and provides a principled method for learning this equilibrium coefficient via reduction to the KL-regularized RL objective, thus allowing for flexible integration into standard fine-tuning p...

Keegan Harris, Brian Lee, Ian Waudby-Smith et al. · arXiv.org · 0 citations