Engineering Dependable and Secure Machine Learning Systems: Third International Workshop, EDSMLS 202
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- Artikel-Nr.: 10341600
Beschreibung
Quality Management of Deep Learning Systems.- Can Attention Masks Improve Adversarial Robustness?.- Learner-Independent Data Omission Attacks.- Extraction of Complex DNN Models: Real Threat or Boogeyman?.- Principal Component Properties of Adversarial Samples.- FreaAI: Automated extraction of data slices to test machine learning models.- Density estimation in representation space to predict model uncertainty.- Automated detection of drift in deep learning based classifiers using network embedding.- Quality of syntactic implication of RL-based sentence summarization.- Dependable Neural Networks for Safety Critical Tasks.
Eigenschaften
Breite: | 155 |
Gewicht: | 244 g |
Höhe: | 8 |
Länge: | 235 |
Seiten: | 141 |
Sprachen: | Englisch |
Autor: | Eitan Farchi, Guy Barash, Onn Shehory |
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