Zobrazeno 1 - 10
of 321
pro vyhledávání: '"Gjergji Kasneci"'
Autor:
Enkelejda Kasneci, Gjergji Kasneci, Tobias Appel, Johannes Haug, Franz Wortha, Maike Tibus, Ulrich Trautwein, Peter Gerjets
Publikováno v:
Scientific Data, Vol 8, Iss 1, Pp 1-14 (2021)
Measurement(s) intelligence • eye movement • Socioeconomic Factors Technology Type(s) culture fair intelligence test (CFT-R) • eye tracking device • Questionnaire Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file
Externí odkaz:
https://doaj.org/article/61ff5de549b94a4c97836f6455c46d62
Autor:
Enkelejda Kasneci, Gjergji Kasneci, Ulrich Trautwein, Tobias Appel, Maike Tibus, Susanne M Jaeggi, Peter Gerjets
Publikováno v:
PLoS ONE, Vol 17, Iss 3, p e0264316 (2022)
Understanding the main factors contributing to individual differences in fluid intelligence is one of the main challenges of psychology. A vast body of research has evolved from the theoretical framework put forward by Cattell, who developed the Cult
Externí odkaz:
https://doaj.org/article/0b60c9daca4c40fda85c8383b62e3db2
Publikováno v:
Computers in Human Behavior Reports, Vol 4, Iss , Pp 100116- (2021)
In recent years, the detection of cognitive load has received a lot of attention. Understanding the circumstances in which cognitive load occurs and reliably predicting such occurrences, offers the potential for considerable advances in the field of
Externí odkaz:
https://doaj.org/article/def24efabc244de1895efba7ce759274
Publikováno v:
International Journal of Data Science and Analytics. 16:85-100
Although deep neural networks (DNNs) constitute the state of the art in many tasks based on visual, audio, or text data, their performance on heterogeneous, tabular data is typically inferior to that of decision tree ensembles. To bridge the gap betw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a3fef5aa9f0abf53592c2b070a4dc0e
https://doi.org/10.1007/s41060-022-00350-z
https://doi.org/10.1007/s41060-022-00350-z
Autor:
Enkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, Maria Bannert, Daryna Dementieva, Frank Fischer, Urs Gasser, Georg Groh, Stephan Günnemann, Eyke Hüllermeier, Stephan Krusche, Gitta Kutyniok, Tilman Michaeli, Claudia Nerdel, Jürgen Pfeffer, Oleksandra Poquet, Michael Sailer, Albrecht Schmidt, Tina Seidel, Matthias Stadler, Jochen Weller, Jochen Kuhn, Gjergji Kasneci
Large language models represent a significant advancement in the field of AI. The underlying technology is key to further innovations and, despite critical views and even bans within communities and regions, large language models are here to stay. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c0e71a2082cc43abdff337c723b54d5
https://doi.org/10.35542/osf.io/5er8f
https://doi.org/10.35542/osf.io/5er8f
Publikováno v:
Medical Image Learning with Limited and Noisy Data ISBN: 9783031167591
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e6bdbe6c8b30b91ed04b154e8c48679b
https://doi.org/10.1007/978-3-031-16760-7_7
https://doi.org/10.1007/978-3-031-16760-7_7
Autor:
Hamed Jalali, Gjergji Kasneci
Publikováno v:
2022 IEEE International Conference on Big Data and Smart Computing (BigComp).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55369121c00ade43a24c441ccf5d6538
https://doi.org/10.1109/bigcomp54360.2022.00014
https://doi.org/10.1109/bigcomp54360.2022.00014
As complex machine learning models are increasingly used in sensitive applications like banking, trading or credit scoring, there is a growing demand for reliable explanation mechanisms. Local feature attribution methods have become a popular techniq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41e27260bcf80a469b09298fd885741c
Autor:
Alejandra Bringas Colmenarejo, Luca Nannini, Alisa Rieger, Kristen M. Scott, Xuan Zhao, Gourab K Patro, Gjergji Kasneci, Katharina Kinder-Kurlanda
Publikováno v:
AIES 2022-Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society
With increasing digitalization, Artificial Intelligence (AI) is becoming ubiquitous. AI-based systems to identify, optimize, automate, and scale solutions to complex economic and societal problems are being proposed and implemented. This has motivate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d542fe66d3da23d7596f824a5a6de3f8
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::666612dff24bd2bb6ae7f2fb7ecc32c3
https://doi.org/10.1109/bigdata52589.2021.9672077
https://doi.org/10.1109/bigdata52589.2021.9672077