Adversarial Robustness Toolbox v1.0.0

Autor: Nicolae, Maria-Irina, Sinn, Mathieu, Tran, Minh Ngoc, Buesser, Beat, Rawat, Ambrish, Wistuba, Martin, Zantedeschi, Valentina, Baracaldo, Nathalie, Chen, Bryant, Ludwig, Heiko, Molloy, Ian M., Edwards, Ben

Adversarial Robustness Toolbox (ART) is a Python library supporting developers and researchers in defending Machine Learning models (Deep Neural Networks, Gradient Boosted Decision Trees, Support Vector Machines, Random Forests, Logistic Regression,

Externí odkaz: http://arxiv.org/abs/1807.01069

Learning from Others: User Anomaly Detection Using Anomalous Samples from Other Users.

Autor: Park, Youngja, Molloy, Ian M., Chari, Suresh N., Xu, Zenglin, Gates, Chris, Li, Ninghi

Publikováno v: Computer Security - ESORICS 2015: 20th European Symposium on Research in Computer Security, Vienna, Austria, September 21-25, 2015, Proceedings, Part II; 2015, p396-414, 19p

Generating Balanced Classifier-Independent Training Samples from Unlabeled Data.

Autor: Park, Youngja, Qi, Zijie, Chari, Suresh N., Molloy, Ian M.

Publikováno v: Advances in Knowledge Discovery & Data Mining (9783642302169); 2012, p266-281, 16p