Search Results for author: Guillaume Martinet

Found 2 papers, 1 papers with code

Variance Minimization in the Wasserstein Space for Invariant Causal Prediction

1 code implementation • 13 Oct 2021 • Guillaume Martinet, Alexander Strzalkowski, Barbara E. Engelhardt

Selecting powerful predictors for an outcome is a cornerstone task for machine learning.

Causal Discovery Causal Inference

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Marginal Singularity, and the Benefits of Labels in Covariate-Shift

no code implementations • 5 Mar 2018 • Samory Kpotufe, Guillaume Martinet

We present new minimax results that concisely capture the relative benefits of source and target labeled data, under covariate-shift.

General Classification

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