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Found 6 papers, 5 papers with code
Differentiable Learning Under Triage
However, the interplay between the prediction accuracy of the model and the human experts under algorithmic triage is not well understood.
Regression Under Human Assistance
In this paper, we take a first step towards the development of machine learning models that are optimized to operate under different automation levels.
Classification Under Human Assistance
Experiments on synthetic and real-world data from several applications in medical diagnosis illustrate our theoretical findings and demonstrate that, under human assistance, supervised learning models trained to operate under different automation levels can outperform those trained for full automation as well as humans operating alone.
Improving Expert Predictions with Conformal Prediction
In this work, we develop an automated decision support system that, by design, does not require experts to understand when to trust the system to improve performance.
On the Within-Group Fairness of Screening Classifiers
Screening classifiers are increasingly used to identify qualified candidates in a variety of selection processes.
Computational Approaches for Stochastic Shortest Path on Succinct MDPs
We consider the stochastic shortest path (SSP) problem for succinct Markov decision processes (MDPs), where the MDP consists of a set of variables, and a set of nondeterministic rules that update the variables.
