zdhnarsil / margin-boosting Goto Github PK
View Code? Open in Web Editor NEWCode for our paper "Building Robust Ensembles via Margin Boosting" (ICML 2022)
License: MIT License
Code for our paper "Building Robust Ensembles via Margin Boosting" (ICML 2022)
License: MIT License
Hi.
I went through the implementation followed your instructions to reproduce your results.
To mainly produce result for wider model (ensemble), what should I do? --individual
is False
?
When each model of an ensemble is appended after each iteration, the new ensemble is trained and updated but only the last (the latest appended model) of the ensemble is saved. Why not all models of the ensemble are saved? If I'm not mistaken, this training scheme will not save the models trained in previous iterations. If I want to load and evaluate the ensemble after the training is finished, it may not reflect the best ensemble. Should save all models or just the last appended?
Thanks
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