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Javier Abad Martinez

2 accepted papers

2024

Hidden yet quantifiable: A lower bound for confounding strength using randomized trials

AISTATS 2024poster

In the era of fast-paced precision medicine, observational studies play a major role in properly evaluating new treatments in clinical practice. Yet, unobserved confounding can significantly compromise causal conclusions drawn from non-randomized data. We propose a novel strategy that leverages rand…

2023

Approximating Full Conformal Prediction at Scale via Influence Functions

AAAI 2023technical

Conformal prediction (CP) is a wrapper around traditional machine learning models, giving coverage guarantees under the sole assumption of exchangeability; in classification problems, a CP guarantees that the error rate is at most a chosen significance level, irrespective of whether the underlying m…