activity
20202022
collaborators

5 papers

cs.AI2022

Combining Deep Learning and Reasoning for Address Detection in Unstructured Text Documents

Matthias Engelbach, Dennis Klau, Jens Drawehn +1

Extracting information from unstructured text documents is a demanding task, since these documents can have a broad variety of different layouts and a non-trivial reading order, li…

cs.CL2021

Evaluation of Representation Models for Text Classification with AutoML Tools

Sebastian Brändle, Marc Hanussek, Matthias Blohm +1

Automated Machine Learning (AutoML) has gained increasing success on tabular data in recent years. However, processing unstructured data like text is a challenge and not widely sup…

cs.AI2021

VitrAI -- Applying Explainable AI in the Real World

Marc Hanussek, Falko Kötter, Maximilien Kintz +1

With recent progress in the field of Explainable Artificial Intelligence (XAI) and increasing use in practice, the need for an evaluation of different XAI methods and their explana…

cs.LG2020

Leveraging Automated Machine Learning for Text Classification: Evaluation of AutoML Tools and Comparison with Human Performance

Matthias Blohm, Marc Hanussek, Maximilien Kintz

Recently, Automated Machine Learning (AutoML) has registered increasing success with respect to tabular data. However, the question arises whether AutoML can also be applied effect…

cs.LG2020

Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark

Marc Hanussek, Matthias Blohm, Maximilien Kintz

In the last few years, Automated Machine Learning (AutoML) has gained much attention. With that said, the question arises whether AutoML can outperform results achieved by human da…