1 citations · 2 across the 2 of their papers we have counts for
3 papers
stat.ML2020★ 1 cited
(Decision and regression) tree ensemble based kernels for regression and classification
Dai Feng, Richard Baumgartner
Tree based ensembles such as Breiman's random forest (RF) and Gradient Boosted Trees (GBT) can be interpreted as implicit kernel generators, where the ensuing proximity matrix repr…
stat.ML2020★ 1 cited
Random Forest (RF) Kernel for Regression, Classification and Survival
Dai Feng, Richard Baumgartner
Breiman's random forest (RF) can be interpreted as an implicit kernel generator,where the ensuing proximity matrix represents the data-driven RF kernel. Kernel perspective on the R…
eess.IV2020
A deep learning-facilitated radiomics solution for the prediction of lung lesion shrinkage in non-small cell lung cancer trials
Antong Chen, Jennifer Saouaf, Bo Zhou +6
Herein we propose a deep learning-based approach for the prediction of lung lesion response based on radiomic features extracted from clinical CT scans of patients in non-small cel…