1 citations · 1 across the 3 of their papers we have counts for
3 papers
Hardware Aware Ensemble Selection for Balancing Predictive Accuracy and Cost
Jannis Maier, Felix Möller, Lennart Purucker
Automated Machine Learning (AutoML) significantly simplifies the deployment of machine learning models by automating tasks from data preprocessing to model selection to ensembling.…
Revealing the Hidden Impact of Top-N Metrics on Optimization in Recommender Systems
Lukas Wegmeth, Tobias Vente, Lennart Purucker
The hyperparameters of recommender systems for top-n predictions are typically optimized to enhance the predictive performance of algorithms. Thereby, the optimization algorithm, e…
Q(D)O-ES: Population-based Quality (Diversity) Optimisation for Post Hoc Ensemble Selection in AutoML
Lennart Purucker, Lennart Schneider, Marie Anastacio +3
Automated machine learning (AutoML) systems commonly ensemble models post hoc to improve predictive performance, typically via greedy ensemble selection (GES). However, we believe…