7 citations · 7 across the 2 of their papers we have counts for
7 papers
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…
Smart buildings as Cyber-Physical Systems: Data-driven predictive control strategies for energy efficiency
Mischa Schmidt, Christer Åhlund
Due to its significant contribution to global energy usage and the associated greenhouse gas emissions, existing building stock's energy efficiency must improve. Predictive buildin…