Tag: independence
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Optimal Prediction-Augmented Algorithms for Testing Independence of Distributions
Optimal Prediction-Augmented Algorithms for Testing Independence of Distributions arXiv:2603.04635v1 Announce Type: new Abstract: Independence testing is a fundamental problem in statistical inference: given samples from a joint distribution $p$ over multiple random variables, the goal is to determine whether $p$ is a product distribution or is $epsilon$-far from all product distributions in total variation distance.…
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On the Hardness of Conditional Independence Testing In Practice
On the Hardness of Conditional Independence Testing In Practice arXiv:2512.14000v1 Announce Type: new Abstract: Tests of conditional independence (CI) underpin a number of important problems in machine learning and statistics, from causal discovery to evaluation of predictor fairness and out-of-distribution robustness. Shah and Peters (2020) showed that, contrary to the unconditional case, no universally finite-sample…
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Amortized Conditional Independence Testing
Amortized Conditional Independence Testing arXiv:2502.20925v1 Announce Type: new Abstract: Testing for the conditional independence structure in data is a fundamental and critical task in statistics and machine learning, which finds natural applications in causal discovery – a highly relevant problem to many scientific disciplines. Existing methods seek to design explicit test statistics that quantify the…