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Found 5 papers, 1 papers with code
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation
Predicting the efficacy of a drug for a given individual, using high-dimensional genomic measurements, is at the core of precision medicine.
Knowledge Elicitation via Sequential Probabilistic Inference for High-Dimensional Prediction
Prediction in a small-sized sample with a large number of covariates, the "small n, large p" problem, is challenging.
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets
The main component of our approach is a user model that models the domain expert's knowledge of the relevance of different features for a prediction task.
Regression with n$\to$1 by Expert Knowledge Elicitation
We consider regression under the "extremely small $n$ large $p$" condition, where the number of samples $n$ is so small compared to the dimensionality $p$ that predictors cannot be estimated without prior knowledge.
Best-Arm Identification in Linear Bandits
We study the best-arm identification problem in linear bandit, where the rewards of the arms depend linearly on an unknown parameter $\theta^*$ and the objective is to return the arm with the largest reward.
