Methods for probabilistic modeling of knowledge elicitation for improving machine learning predictions

Press/Media: Media appearance

Period	4 Dec 2020

Media coverage

1

Media coverage

Title	Methods for probabilistic modeling of knowledge elicitation for improving machine learning predictions
Media name/outlet	Aaltodoc
Country/Territory	Finland
Date	04/12/2020
URL	https://aaltodoc.aalto.fi/handle/123456789/87765
Persons	Samuel Kaski

Publications and artistic outputs
Visualizations relevant to the user by multi-view latent variable factorization
Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
A decision-theoretic approach for model interpretability in Bayesian framework
Research output: Contribution to journal › Article › Scientific › peer-review
Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge
Research output: Contribution to journal › Article › Scientific › peer-review
Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction
Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets
Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review