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1 Ergebnisse
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MODE: automated neural network model debugging via state di..:
, In:
Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
,
Ma, Shiqing
;
Liu, Yingqi
;
Lee, Wen-Chuan
.. - p. 175-186 , 2018
Link:
https://dl.acm.org/doi/10.1145/3236024.3236082
RT T1 <cTitle>Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering</cTitle>: T1 <Title>MODE: automated neural network model debugging via state differential analysis and input selection</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3236082&Exemplar=1&LAN=DE A1 Ma, Shiqing A1 Liu, Yingqi A1 Lee, Wen-Chuan A1 Zhang, Xiangyu A1 Grama, Ananth PB ACM YR 2018 K1 Debugging K1 Deep Neural Network K1 Differential Analysis K1 Software and its engineering K1 Software creation and management K1 Software verification and validation K1 Software defect analysis K1 Software testing and debugging K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Neural networks SP 175 OP 186 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3236024.3236082 DO https://dl.acm.org/doi/10.1145/3236024.3236082 SF ELIB - SuUB Bremen
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