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Found 5 papers, 1 papers with code
Orthogonal Series Estimation for the Ratio of Conditional Expectation Functions
This chapter develops the general framework for estimation and inference on CEFR, which allows the use of flexible machine learning for infinite-dimensional nuisance parameters.
Estimation of Local Average Treatment Effect by Data Combination
However, model selection and hyperparameter tuning for the direct least squares estimator can be unstable in practice since it is defined as a solution to the minimax problem.
Bayesian data combination model with Gaussian process latent variable model for mixed observed variables under NMAR missingness
In the analysis of observational data in social sciences and businesses, it is difficult to obtain a "(quasi) single-source dataset" in which the variables of interest are simultaneously observed.
Positive-Unlabelled Survival Data Analysis
In this paper, we consider a novel framework of positive-unlabeled data in which as positive data survival times are observed for subjects who have events during the observation time as positive data and as unlabeled data censoring times are observed but whether the event occurs or not are unknown for some subjects.
Fatigue-Aware Ad Creative Selection
In online display advertising, selecting the most effective ad creative (ad image) for each impression is a crucial task for DSPs (Demand-Side Platforms) to fulfill their goals (click-through rate, number of conversions, revenue, and brand improvement).
