Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Christoph Doell"'
Autor:
Prosenjit Bose, Kai Dannies, Jean-Lou De Carufel, Christoph Doell, Carsten Grimm, Anil Maheshwari, Stefan Schirra, Michiel Smid
Publikováno v:
Journal of Computational Geometry, Vol 4, Iss 1 (2013)
Consider the continuum of points along the edges of a network, i.e., an undirected graph with positive edge weights. We measure distance between these points in terms of the shortest path distance along the network, known as the network distance. Wit
Externí odkaz:
https://doaj.org/article/df67c8eef48f4528b47467088e7a6a82
Autor:
Christoph Doell, Christian Borgelt
Publikováno v:
SSCI
Aggregation methods have been studied extensively from a mathematical, theoretical point of view. In this work, however, we focus on a more practical aspect: subclassifications. Given class predictions for several sub-objects of a single instance, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a09b3ba4feac1d0b9439e39cee9a38e
https://doi.org/10.1109/ssci44817.2019.9002806
https://doi.org/10.1109/ssci44817.2019.9002806
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030374938
ICAART (Revised Selected Papers)
ICAART (Revised Selected Papers)
For the last decade, Deep Reinforcement Learning (DRL) has undergone very rapid development. However, less has been done to integrate linear methods into it. Our research aims at a simple and practical Wide and Deep Reinforcement Learning framework t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc2a2965ae04ba6d7b7d46b19a35780b
https://doi.org/10.1007/978-3-030-37494-5_12
https://doi.org/10.1007/978-3-030-37494-5_12
Autor:
Christoph Doell, Sophie Siebert
Publikováno v:
BICA
Cognitive architectures are frequently built to model naturally intelligent behavior. This aims on two primary goals: On one hand these architectures model human behavior in order to give a better understanding of the human thought process. On the ot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d56257d6fc3b484df570c0e4216e8c2a
https://doi.org/10.1016/j.procs.2016.07.419
https://doi.org/10.1016/j.procs.2016.07.419
Publikováno v:
SSCI
We investigate the differences in brain signals of craving smokers, non-craving smokers, and non-smokers. To this end, we use data from resting-state EEG measurements to train predictive models to distinguish these three groups. We improve the neural
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5b8d298d3ed8d2e8b0ac9efd9a23917
https://doi.org/10.1109/ssci.2018.8628678
https://doi.org/10.1109/ssci.2018.8628678
Publikováno v:
Advances in Intelligent Data Analysis XVII ISBN: 9783030017675
IDA
IDA
In the present study, we investigate the differences in brain signals of craving smokers, non-craving smokers, and non-smokers. To this end, we use data from resting-state EEG measurements to train predictive models to distinguish these three groups.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::90856cc3bcaeca3a9824088ca468bedb
https://doi.org/10.1007/978-3-030-01768-2_7
https://doi.org/10.1007/978-3-030-01768-2_7
Publikováno v:
SSCI
This work builds up on previous research by Sievers and Helmert, who developed an Monte Carlo Tree Search based doppelkopf agent. This four player card game features a larger state space than skat due to the unknown cards of the contestants. Addition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2d06cef812ccdbb64c003265be2ae5f
https://doi.org/10.1109/ssci.2017.8285181
https://doi.org/10.1109/ssci.2017.8285181
Publikováno v:
SSCI
This work aims to scrutinise a proprietary dataset containing major accidents occurred in high-technology facilities, in order to disclose relevant features and indicate a path to the recognition of the genesis of human errors. The application of a t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b9b3a1b511e8c72158ebf9e339ecab2
https://doi.org/10.1109/ssci.2015.256
https://doi.org/10.1109/ssci.2015.256