E-LIB Suche - Ergebnisse für: Stegherr, Helena

1

Discovering rules for rule-based machine learning with the ..:

Heider, Michael ; Stegherr, Helena ; Pätzel, David...
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/109780. , 2023

Link: https://opus.bibliothek...

2

Assisting convergence behaviour characterisation with unsup..:

Stegherr, Helena ; Heider, Michael ; Hähner, Jörg
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/110315. , 2023

Link: https://opus.bibliothek...

3

Assessing model requirements for explainable AI: a template..:

Heider, Michael ; Stegherr, Helena ; Nordsieck, Richard.
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/109712. , 2023

Link: https://opus.bibliothek...

4

A framework for modular construction and evaluation of meta..:

Stegherr, Helena ; Luley, Leopold ; Wurth, Jonathan..
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/103452. , 2023

Link: https://opus.bibliothek...

5

Investigating the impact of independent rule fitnesses in a..:

Heider, Michael ; Stegherr, Helena ; Wurth, Jonathan..
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/103973. , 2022

Link: https://opus.bibliothek...

6

Comparing different metaheuristics for model selection in a..:

Wurth, Jonathan ; Heider, Michael ; Stegherr, Helena..
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/97477. , 2022

Link: https://opus.bibliothek...

7

Classifying metaheuristics: towards a unified multi-level c..:

Stegherr, Helena ; Heider, Michael ; Hähner, Jörg
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/83237. , 2022

Link: https://opus.bibliothek...

8

Explainability Requirements in Edge Band Manufacturing---In..:

Heider, Michael ; Stegherr, Helena
doi:10.5281/zenodo.6505009. , 2022

Link: https://zenodo.org/recor..

9

Learning Classifier Systems for Self-Explaining Socio-Techn..:

Heider, Michael ; Stegherr, Helena ; Nordsieck, Richard.
http://arxiv.org/abs/2207.02300. , 2022

Link: http://arxiv.org/abs/220..

10

Approaches for rule discovery in a learning classifier syst..:

Heider, Michael ; Stegherr, Helena ; Pätzel, David...
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/104138. , 2022

Link: https://opus.bibliothek...

11

Separating rule discovery and global solution composition i..:

Heider, Michael ; Stegherr, Helena ; Wurth, Jonathan..
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/97476. , 2022

Link: https://opus.bibliothek...

12

Investigating the Impact of Independent Rule Fitnesses in a..:

Heider, Michael ; Stegherr, Helena ; Wurth, Jonathan..
http://arxiv.org/abs/2207.05582. , 2022

Link: http://arxiv.org/abs/220..

13

Separating Rule Discovery and Global Solution Composition i..:

Heider, Michael ; Stegherr, Helena ; Wurth, Jonathan..
http://arxiv.org/abs/2202.01677. , 2022

Link: http://arxiv.org/abs/220..

14

Analysing metaheuristic components:

Stegherr, Helena ; Hähner, Jörg
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/90779. , 2021

Link: https://opus.bibliothek...

15

Design of large-scale metaheuristic component studies:

Stegherr, Helena ; Heider, Michael ; Luley, Leopold.
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/90775. , 2021

Link: https://opus.bibliothek...