Kathrin Grosse
Cited by
Cited by
Adversarial examples for malware detection
K Grosse, N Papernot, P Manoharan, M Backes, P McDaniel
European symposium on research in computer security, 62-79, 2017
On the (statistical) detection of adversarial examples
K Grosse, P Manoharan, N Papernot, M Backes, P McDaniel
arXiv preprint arXiv:1702.06280, 2017
Mlcapsule: Guarded offline deployment of machine learning as a service
L Hanzlik, Y Zhang, K Grosse, A Salem, M Augustin, M Backes, M Fritz
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
Integrating argumentation and sentiment analysis for mining opinions from Twitter
K Grosse, MP Gonzalez, CI Chesnevar, AG Maguitman
AI Communications 28 (3), 387-401, 2015
The limitations of model uncertainty in adversarial settings
K Grosse, D Pfaff, MT Smith, M Backes
arXiv preprint arXiv:1812.02606, 2018
An Argument-based Approach to Mining Opinions from Twitter.
K Grosse, CI Chesņevar, AG Maguitman
AT 918, 408-422, 2012
On the security relevance of initial weights in deep neural networks
K Grosse, TA Trost, M Mosbach, M Backes, D Klakow
International Conference on Artificial Neural Networks, 3-14, 2020
Empowering an e-government platform through twitter-based arguments
C Chesņevar, E Estevez, K Grosse, A Maguitman
Inteligencia Artificial. Revista Iberoamericana de Inteligencia Artificial …, 2012
Backdoor smoothing: Demystifying backdoor attacks on deep neural networks
K Grosse, T Lee, B Biggio, Y Park, M Backes, I Molloy
Computers & Security 120, 102814, 2022
Adversarial vulnerability bounds for gaussian process classification
MT Smith, K Grosse, M Backes, MA Alvarez
Machine Learning, 1-39, 2022
Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning
AE Cinā, K Grosse, A Demontis, S Vascon, W Zellinger, BA Moser, ...
arXiv preprint arXiv:2205.01992, 2022
Killing four birds with one Gaussian process: the relation between different test-time attacks
K Grosse, MT Smith, M Backes
2020 25th International Conference on Pattern Recognition (ICPR), 4696-4703, 2021
Backdoor learning curves: Explaining backdoor poisoning beyond influence functions
AE Cinā, K Grosse, S Vascon, A Demontis, B Biggio, F Roli, M Pelillo
arXiv preprint arXiv:2106.07214, 2021
Industrial practitioners' mental models of adversarial machine learning
L Bieringer, K Grosse, M Backes, B Biggio, K Krombholz
Eighteenth Symposium on Usable Privacy and Security (SOUPS 2022), 97-116, 2022
Measuring Overfitting of Machine Learning Computer Model and Susceptibility to Security Threats
K Grosse, T Lee, Y Park, IM Molloy
US Patent App. 16/833,884, 2021
Do winning tickets exist before DNN training?
K Grosse, M Backes
Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021
A first approach to mining opinions as multisets through argumentation
CI Chesnevar, MP González, K Grosse, AG Maguitman
Agreement Technologies, 195-209, 2013
Machine Learning Security against Data Poisoning: Are We There Yet?
AE Cinā, K Grosse, A Demontis, B Biggio, F Roli, M Pelillo
arXiv preprint arXiv:2204.05986, 2022
Summarising Event Sequences using Serial Episodes and an Ontology
K Grosse, J Vreeken
Proceedings of the Workshop on Interactions between Data Mining and Natural …, 2017
A First Approach Towards Integrating Twitter and Defeasible Argumentation
K Grosse, CI Chesņevar
XIII Argentine Symposium on Artificial Intelligence (ASAI 2012)(XLII JAIIO …, 2012
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