7 citations · 7 across the 2 of their papers we have counts for
5 papers · 1 filter
A study on Ensemble Learning for Time Series Forecasting and the need for Meta-Learning
Julia Gastinger, Sébastien Nicolas, Dušica Stepić +2
The contribution of this work is twofold: (1) We introduce a collection of ensemble methods for time series forecasting to combine predictions from base models. We demonstrate insi…
The Combinatorial Multi-Bandit Problem and its Application to Energy Management
Tobias Jacobs, Mischa Schmidt, Sébastien Nicolas +1
We study a Combinatorial Multi-Bandit Problem motivated by applications in energy systems management. Given multiple probabilistic multi-arm bandits with unknown outcome distributi…
HAMLET -- A Learning Curve-Enabled Multi-Armed Bandit for Algorithm Selection
Mischa Schmidt, Julia Gastinger, Sébastien Nicolas +1
Automated algorithm selection and hyperparameter tuning facilitates the application of machine learning. Traditional multi-armed bandit strategies look to the history of observed r…
A Study of the Learning Progress in Neural Architecture Search Techniques
Prabhant Singh, Tobias Jacobs, Sebastien Nicolas +1
In neural architecture search, the structure of the neural network to best model a given dataset is determined by an automated search process. Efficient Neural Architecture Search…
On the Performance of Differential Evolution for Hyperparameter Tuning
Mischa Schmidt, Shahd Safarani, Julia Gastinger +3
Automated hyperparameter tuning aspires to facilitate the application of machine learning for non-experts. In the literature, different optimization approaches are applied for that…