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Found 3 papers, 2 papers with code
Conditional independence testing: a predictive perspective
Conditional independence testing is a key problem required by many machine learning and statistics tools.
Quantification under prior probability shift: the ratio estimator and its extensions
The quantification problem consists of determining the prevalence of a given label in a target population.
Learning with many experts: model selection and sparsity
Next, we discuss how this loss can be used to tune a penalization which introduces sparsity in the parameters of a traditional class of models.
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