Zobrazeno 1 - 10
of 234
pro vyhledávání: '"Stefan Wrobel"'
Publikováno v:
Visual Informatics, Vol 5, Iss 1, Pp 23-42 (2021)
The word ‘pattern’ frequently appears in the visualisation and visual analytics literature, but what do we mean when we talk about patterns? We propose a practicable definition of the concept of a pattern in a data distribution as a combination o
Externí odkaz:
https://doaj.org/article/00bc96142e6847ab99c59a6f4c5c5e77
This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is
Publikováno v:
Machine Learning.
Despite of its importance for safe machine learning, uncertainty quantification for neural networks is far from being solved. State-of-the-art approaches to estimate neural uncertainties are often hybrid, combining parametric models with explicit or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c245f5e6777583b4a742dfb327060892
https://doi.org/10.1007/s10994-022-06230-8
https://doi.org/10.1007/s10994-022-06230-8
Autor:
Dov Te'eni, Atreyi Kankanhalli, Stefan Wrobel, M. Lynne Markus, Claudia Loebbecke, Omar A. El Sawy, Pernille Rydén, Astrid Obeng-Antwi
Publikováno v:
Loebbecke, C, El Sawy, O, Kankanhalli, A, Lynne Markus, M, Te'Eni, D, Wrobel, S, Rydén, P & Obeng-Antwi, A 2020, ' Artificial intelligence meets is researchers: Can it replace us? ', Communications of the Association for Information Systems, vol. 47 . https://doi.org/10.17705/1CAIS.04713
Given we live in an era with accelerating digitization and rapid advances in artificial intelligence (AI), AI may eventually automate more job tasks. However, researchers have scarcely if at all critically analyzed how AI will automate such tasks and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b59a2715a9e77888ff600a9220ea6c55
https://doi.org/10.17705/1cais.04713
https://doi.org/10.17705/1cais.04713
Autor:
Dorina Weichert, Alexander Kister, Sebastian Houben, Peter Volbach, Marcus Trost, Johannes Hartung, Alexander Bergner, Stefan Wrobel
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efb24b6f5b18863181e45617f6cc7d4d
https://doi.org/10.2139/ssrn.4180760
https://doi.org/10.2139/ssrn.4180760
Artificial intelligence is increasingly penetrating industrial applications as well as areas that affect our daily lives. As a consequence, there is a need for criteria to validate whether the quality of AI applications is sufficient for their intend
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68318f31df11994c362b3a1adb6dd811
Publikováno v:
Designing Data Spaces ISBN: 9783030939748
Machine learning and artificial intelligence have become crucial factors for the competitiveness of individual companies and entire economies. Yet their successful deployment requires access to a large volume of training data often not even available
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::700987aa79b07ebd57fb809abddcb29f
https://doi.org/10.1007/978-3-030-93975-5_13
https://doi.org/10.1007/978-3-030-93975-5_13
Publikováno v:
Discovery Science ISBN: 9783031188398
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::82b55f2ea5120c1fe05194010ef97985
https://doi.org/10.1007/978-3-031-18840-4_34
https://doi.org/10.1007/978-3-031-18840-4_34
Publikováno v:
Machine Learning. 108:1137-1164
Motivated by the impressive predictive power of simple patterns, we consider the problem of mining frequent subtrees in arbitrary graphs. Although the restriction of the pattern language to trees does not resolve the computational complexity of frequ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::582e86a3124415dafa90ec0778753dfd
https://doi.org/10.1007/s10994-019-05779-1
https://doi.org/10.1007/s10994-019-05779-1
Publikováno v:
ICPR
Decision trees excel at interpretability of their prediction results. To achieve required prediction accuracies, however, often large ensembles of decision trees - random forests - are considered, reducing interpretability due to large size. Addition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b704f382e7aec06518115c28ce5245b
https://doi.org/10.1109/icpr48806.2021.9412025
https://doi.org/10.1109/icpr48806.2021.9412025