Zobrazeno 1 - 10
of 366
pro vyhledávání: '"Kristian Kersting"'
Publikováno v:
Frontiers in Artificial Intelligence, Vol 6 (2023)
We consider the problem of learning with sensitive features under the privileged information setting where the goal is to learn a classifier that uses features not available (or too sensitive to collect) at test/deployment time to learn a better mode
Externí odkaz:
https://doaj.org/article/5221005c5eba4d62893651d211111a2f
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 2, p 025069 (2024)
The number of satellites in orbit around Earth is increasing rapidly, with the risk of collision rising accordingly. Trends of the global population of satellites need to be analyzed to test the viability and impact of proposed rules and laws affecti
Externí odkaz:
https://doaj.org/article/262ac9df6e9e4a658c3948106d6fd5ef
Publikováno v:
Remote Sensing, Vol 16, Iss 2, p 266 (2024)
Natural gas pipelines represent a critical infrastructure for most countries and thus their safety is of paramount importance. To report potential risks along pipelines, several steps are taken such as manual inspection and helicopter flights; howeve
Externí odkaz:
https://doaj.org/article/7a4c259990f443838dda31a64656ad40
Publikováno v:
Frontiers in Artificial Intelligence, Vol 6 (2023)
In recent years, deep neural networks for strategy games have made significant progress. AlphaZero-like frameworks which combine Monte-Carlo tree search with reinforcement learning have been successfully applied to numerous games with perfect informa
Externí odkaz:
https://doaj.org/article/a4162a50373341c681131cbdecb4e585
Autor:
Sandra Schwegmann, Janosch Faulhaber, Sebastian Pfaffel, Zhongjie Yu, Martin Dörenkämper, Kristian Kersting, Julia Gottschall
Publikováno v:
Energy and AI, Vol 11, Iss , Pp 100209- (2023)
As wind is the basis of all wind energy projects, a precise knowledge about its availability is needed. For an analysis of the site-specific wind conditions, Virtual Meteorological Masts (VMMs) are frequently used. VMMs make use of site calibrated nu
Externí odkaz:
https://doaj.org/article/f08c09644eb24611af4a2a630771979c
Publikováno v:
Frontiers in Artificial Intelligence, Vol 5 (2022)
Data-driven approaches are becoming increasingly common as problem-solving tools in many areas of science and technology. In most cases, machine learning models are the key component of these solutions. Often, a solution involves multiple learning mo
Externí odkaz:
https://doaj.org/article/c7a9d6ac873d4cfb86c306c66decfcc1
Autor:
Niyati Rawal, Dorothea Koert, Cigdem Turan, Kristian Kersting, Jan Peters, Ruth Stock-Homburg
Publikováno v:
Frontiers in Robotics and AI, Vol 8 (2022)
The ability of a robot to generate appropriate facial expressions is a key aspect of perceived sociability in human-robot interaction. Yet many existing approaches rely on the use of a set of fixed, preprogrammed joint configurations for expression g
Externí odkaz:
https://doaj.org/article/2696175e77524023b76534b62642b7d3
Publikováno v:
Frontiers in Robotics and AI, Vol 8 (2021)
Externí odkaz:
https://doaj.org/article/1648a099954943d38b5e5bd737073cc5
Autor:
Sophie Burkhardt, Jannis Brugger, Nicolas Wagner, Zahra Ahmadi, Kristian Kersting, Stefan Kramer
Publikováno v:
Frontiers in Artificial Intelligence, Vol 4 (2021)
Classification approaches that allow to extract logical rules such as decision trees are often considered to be more interpretable than neural networks. Also, logical rules are comparatively easy to verify with any possible input. This is an importan
Externí odkaz:
https://doaj.org/article/f049da3d036c443e8a8677b9f1b9dc34
Publikováno v:
Frontiers in Artificial Intelligence, Vol 3 (2020)
Allowing machines to choose whether to kill humans would be devastating for world peace and security. But how do we equip machines with the ability to learn ethical or even moral choices? In this study, we show that applying machine learning to human
Externí odkaz:
https://doaj.org/article/f3d987797b9346628b60961cdbfed3ff