Robust Optimization for Adversarial Deep Learning
März, Lars Steffen ; Ulbrich, Stefan 2024 Universitäts- und Landesbibliothek
- Link zu diesem Datensatz
- https://d-nb.info/1323405836
- Titel
- Robust Optimization for Adversarial Deep Learning
- Art des Inhalts
- Monographie
- Verfassangaben
- Lars Steffen März ; Betreuer: Stefan Ulbrich
- Autor(en)
-
- März, Lars Steffen
- Ulbrich, Stefan
- Verlag
- Darmstadt : Universitäts- und Landesbibliothek [2024]
- Jahr
- Erscheinungsdatum: 2024
- Umfang/Format
- Online-Ressource
- DOI
- 10.26083/tuprints-00026745
- Online
- https://doi.org/10.26083/tuprints-00026745
- Sprache
- eng
- Schlagwörter
-
- robust optimization
- stochastic optimization
- distributionally robust optimization
- adversarial deep learning
- adversarial examples
- adversarial samples
- adversarial robustness
- deep learning
- np-hard
- np hard
- np-hardness
- np hardness
- Danskin's Theorem
- BOBYQA
- FGSM
- Fast Gradient Sign Method
- PGD
- Projected Gradient Descent
- SGD
- Stochastic Gradient Descent
- black-box attack
- white-box attack
- image classification
- ImageNet
- CIFAR
- CIFAR-10
- gaussian smoothing
- cross-entropy loss
- CEL
- ILSVRC
- adversarial perturbation
- p-norm
- p norm
- certified robustness
- noise injection
- randomized smoothing
- gradient masking
- gradient obfuscation
- catastrophic overfitting
- cosine similarity
- step size
- step length
- harmonic
- geometric
- rescaling
- Stand
- 30.11.2025 12:58
- Im Katalog seit
- 07.03.2026