• Corpus ID: 162183474

Automated Algorithm Selection - Predict which algorithm to use!

@inproceedings{Lindauer2019AutomatedAS,
  title={Automated Algorithm Selection - Predict which algorithm to use!},
  author={Marius Thomas Lindauer},
  booktitle={AMIR@ECIR},
  year={2019}
}

• M. Lindauer
• Published in AMIR@ECIR 2019
• Computer Science

To achieve state-of-the-art performance, it is often crucial to select a suitable algorithm for a given problem instance. For example, what is the best search algorithm for a given instance of a search problem; or what is the best machine learning algorithm for a given dataset? By trying out many different algorithms on many problem instances, developers learn an intuitive mapping from some characteristics of a given problem instance (e.g., the number of features of a dataset) to a well-performing algorithm (e.g., random forest). The goal of automated algorithm selection is to learn from data, how to automatically select a well-performing algorithm given such characteristics. In this talk, I will give an overview of the key ideas behind algorithm selection and different approaches addressing this problem by using machine learning.