2 papers
cs.LG2024
Deciphering AutoML Ensembles: cattleia's Assistance in Decision-Making
Anna Kozak, Dominik Kędzierski, Jakub Piwko +2
In many applications, model ensembling proves to be better than a single predictive model. Hence, it is the most common post-processing technique in Automated Machine Learning (Aut…
cs.LG2024
Rethinking of Encoder-based Warm-start Methods in Hyperparameter Optimization
Dawid Płudowski, Antoni Zajko, Anna Kozak +1
Effectively representing heterogeneous tabular datasets for meta-learning purposes remains an open problem. Previous approaches rely on predefined meta-features, for example, stati…