Inhaltsbereich
Hornung, Roman
- Hornung R. (2022): Diversity Forests: Using split sampling to enable innovative complex split procedures in random forests. DAGStat 2022. Hamburg, Germany, 28.03.–01.04.2022. Talklet
- Hapfelmeier A., Hornung R., Haller B. (2022): Sequential permutation testing of random forest variable importance measures. DAGStat 2022. Hamburg, Germany, 28.03.–01.04.2022. Poster
- Hornung R., Boulesteix A.-L. (2021): Interaction forests: Identifying and exploiting interpretable quantitative and qualitative interaction effects. ROeS 2021. Salzburg, Austria, 07.–10.09.2021.
- Hornung R. (2021): Interaction forests: Identifying and exploiting interpretable quantitative and qualitative interaction effects. Biometrisches Kolloquium 2021. Münster, Germany, 14.–17.03.2021.
- Hornung R. (2020): Ordinal forests: Prediction and covariate importance ranking with ordinal response variables. CMStatistics 2020. London, England, 19.–21.12.2020. Invited Talk
- Ellenbach N., Boulesteix A.-L., Bischl B., Unger K., Hornung R. (2019): Improved outcome prediction across data sources through robust parameter tuning. Statistical Computing 2019. Günzburg, Germany, 30.06.–03.07.2019. Talk
- Hornung R., Wright M. (2019): Block Forests: random forests for blocks of clinical and omics covariate data. DAGStat 2019. Muenchen, Germany, 18.–22.03.2019. Talk
- Hornung R., Wright M. (2018): Random forests for multi-omics data. Statistical Computing 2018. Günzburg, Germany, 08.–11.07.2018. Talk
- Klau S., Jurinovic V., Hornung R., Herold T., Boulesteix A.L. (2018): Priority-Lasso: a simple hierarchical approach to the prediction of clinical outcome using multi-omics data. Biometrisches Kolloquium 2018. Frankfurt, Germany, 25.–28.03.2018. Talk
- Boulesteix A.-L., Janitza S., Hornung R., Probst P., Busen H., Hapfelmeier A. (2017): Are published complex prediction rules currently applicable for readers? A survey of applied random forest literature and recommendations. CEN ISBS 2017. Wien, Austria, 28.08.2017–01.09.2017. Talk
- Hornung R. (2017): Ordinal Forests: A versatile tool for ordinal regression. Statistical Computing 2017. Günzburg, Germany, 23.–25.07.2017. Talk
- Hornung R., Jurinovic V., Metzeler K., Rothenberg-Thurley M., Ksienzyk B., Hartmann L., Greif P., Amler S., Schneider S., Sauerland M., Büchner T., Berdel W., Woermann B., Subklewe M., Fiegl M., Bohlander S., Braess J., Hiddemann W., Mansmann U., Spiekermann K., Boulesteix A.-L., Herold T. (2016): Identification and comparison of variables responsible for the indirect in uence of RUNX1 alterations on the survival of patients with acute myeloid leukemia. Wissenschaftliches Symposium der Med. Klinik III 2016. Herrsching, Germany, 22.-23.07.2016. Poster
- Hornung R., Causeur D., Boulesteix A.-L. (2015): Improved cross-study prediction through batch effect adjustment. Biometrisches Kolloquium 2015. Dortmund, Germany, 15.–18.03.2015. Talk
- Hornung R., Bernau C., Truntzer C., Stadler T., Boulesteix A.-L. (2014): Full versus incomplete cross-validation: measuring the impact of imperfect separation between training and test sets in prediction error estimation. Dresden University of Technology. 28.08.2014. Invited Talk
- Hornung R., Bernau C., Truntzer C., Stadler T., Boulesteix A.-L. (2014): Full versus incomplete cross-validation: measuring the impact of imperfect separation between training and test sets in prediction error estimation. Heidelberg University. 07.07.2014. Invited Talk
- Hornung R., Janitza S., El Hadad A., Boulesteix A.-L. (2014): The integrated Brier score as an appropriate error measure in the variable importance of Random Survival Forests. Biometrisches Kolloquium 2014. Bremen, Germany, 10.–13.03.2014. Talk
- Hornung R., Bernau C., Truntzer C., Stadler T., Boulesteix A.-L. (2013): A new measure of the impact of incomplete cross validation, with applications to various steps of prediction rule construction. DAGStat 2013. Freiburg, Germany, 18.–23.03.2013. Poster
- Hornung R., Causeur D., Boulesteix A.-L. (2013): Batch removal methods incorporating latent factor models to account for batch-specific correlation structures. Statistical Methods for (post-) Genomics Data 2013. Amsterdam, the Netherlands, 24.–25.01.2013. Poster
- Hornung R., Causeur D., Boulesteix A.-L. (2012): Batch removal methods incorporating latent factor models to account for batch-specific correlation structures. Building and Evaluating Prognostic Models 2012. Mainz, Germany, 24.–25.09.2012. Poster
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