Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Stefan Faußer"'
Autor:
Dany Meyer, Stefan Fausser
Publikováno v:
ICERI2022 Proceedings.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70543f76c03a25772612955ac770e80e
https://doi.org/10.21125/iceri.2022.1911
https://doi.org/10.21125/iceri.2022.1911
Autor:
Uwe Messer, Stefan Faußer
Publikováno v:
Automatisierung und Personalisierung von Dienstleistungen ISBN: 9783658301675
In this article we focus on Machine Learning in services and introduce a framework for Machine-Learning-Infusion (ML-infusion) in service processes. We introduce basic machine learning tasks, outline the differences between Machine Learning (ML) and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9b0ab5b85754a6cfef18cbf57134479
https://doi.org/10.1007/978-3-658-30168-2_14
https://doi.org/10.1007/978-3-658-30168-2_14
Autor:
Friedhelm Schwenker, Stefan Faußer
Publikováno v:
Neurocomputing. 169:350-357
Ensemble models can achieve more accurate and robust predictions than single learners. A selective ensemble may further improve the predictions by selecting a subset of the models from the entire ensemble, based on a quality criterion. We consider re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::99350a347c62f9aab58597f68e6fd484
https://doi.org/10.1016/j.neucom.2014.11.075
https://doi.org/10.1016/j.neucom.2014.11.075
Autor:
Stefan Faußer, Friedhelm Schwenker
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783642282577
PSL
PSL
Collecting unlabelled data is often effortless while labelling them can be difficult. Either the amount of data is too large or samples cannot be assigned a specific class label with certainty. In semi-supervised clustering the aim is to set the clus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f68c065e9d34e65b8d67a9a3bf7a9ae7
https://doi.org/10.1007/978-3-642-28258-4_8
https://doi.org/10.1007/978-3-642-28258-4_8
Autor:
Stefan Faußer, Friedhelm Schwenker
Publikováno v:
Multiple Classifier Systems ISBN: 9783642215568
MCS
MCS
Ensemble methods allow to combine multiple models to increase the predictive performances but mostly utilize labelled data. In this paper we propose several ensemble methods to learn a combined parameterized state-value function of multiple agents. F
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59832f837a0296bbed5c52df0d0ca4fe
https://doi.org/10.1007/978-3-642-21557-5_8
https://doi.org/10.1007/978-3-642-21557-5_8
Autor:
Stefan Fausser, Friedhelm Schwenker
Publikováno v:
ICPR
Having a large game-tree complexity and being EXPTIME-complete, English Draughts, recently weakly solved during almost two decades, is still hard to learn for intelligent computer agents. In this paper we present a Temporal-Difference method that is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ef47bfafcfbc1612cf63fc0f5892a90
https://doi.org/10.1109/icpr.2010.717
https://doi.org/10.1109/icpr.2010.717
Autor:
Stefan Faußer, Friedhelm Schwenker
Publikováno v:
Artificial Neural Networks in Pattern Recognition ISBN: 9783642121586
ANNPR
ANNPR
Kernel based clustering methods allow to unsupervised partition samples in feature space but have a quadratic computation time O(n2) where n are the number of samples. Therefore these methods are generally ineligible for large datasets. In this paper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a889f8f1cfb4bd70a0e964d2fd50a470
https://doi.org/10.1007/978-3-642-12159-3_12
https://doi.org/10.1007/978-3-642-12159-3_12
Autor:
Stefan Faußer, Friedhelm Schwenker
Publikováno v:
Artificial Neural Networks in Pattern Recognition ISBN: 9783540699385
ANNPR
ANNPR
To win a board-game or more generally to gain something specific in a given Markov-environment, it is most important to have a policy in choosing and taking actions that leads to one of several qualitative good states. In this paper we describe a nov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e3d7e636060bcf65adab907b291eacb7
https://doi.org/10.1007/978-3-540-69939-2_9
https://doi.org/10.1007/978-3-540-69939-2_9