Pranav Mani

2 accepted papers

2026

No Free Lunch: Non-Asymptotic Analysis of Prediction-Powered Inference

Pranav Mani, Peng Xu, Zachary Lipton, Michael Oberst

ICML 2026poster

Prediction-Powered Inference (PPI) is a popular strategy for combining gold-standard and possibly noisy pseudo-labels to perform statistical estimation. Prior work has shown an asymptotic \enquote{free lunch} for PPI++, an adaptive form of PPI, showing that the \textit{asymptotic} variance of PPI++ …

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2022

Unsupervised Learning under Latent Label Shift

Manley Roberts, Pranav Mani, Saurabh Garg, Zachary Chase Lipton

NeurIPS 2022accept

What sorts of structure might enable a learner to discover classes from unlabeled data? Traditional approaches rely on feature-space similarity and heroic assumptions on the data. In this paper, we introduce unsupervised learning under Latent Label Shift (LLS), where the label marginals $p_d(y)$ shi…

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