Search Results for author:
Found 4 papers, 1 papers with code
A study on Ensemble Learning for Time Series Forecasting and the need for Meta-Learning
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.
The Combinatorial Multi-Bandit Problem and its Application to Energy Management
For our energy management application we propose a range of algorithms that combine exploration principles for multi-arm bandits with mathematical programming.
HAMLET -- A Learning Curve-Enabled Multi-Armed Bandit for Algorithm Selection
Automated algorithm selection and hyperparameter tuning facilitates the application of machine learning.
On the Performance of Differential Evolution for Hyperparameter Tuning
This empirical study involves a range of different machine learning algorithms and datasets with various characteristics to compare the performance of Differential Evolution with Sequential Model-based Algorithm Configuration (SMAC), a reference Bayesian Optimization approach.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
