| Anomaly detection with robust deep autoencoders C Zhou, RC Paffenroth Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 1594 | 2017 |
| Generative adversarial active learning for unsupervised outlier detection Y Liu, Z Li, C Zhou, Y Jiang, J Sun, M Wang, X He IEEE Transactions on Knowledge and Data Engineering 32 (8), 1517-1528, 2019 | 368 | 2019 |
| Modern machine learning for cyber-defense and distributed denial-of-service attacks RC Paffenroth, C Zhou IEEE Engineering Management Review 47 (4), 80-85, 2019 | 16 | 2019 |
| Boosting gene expression clustering with system-wide biological information: a robust autoencoder approach H Cui, C Zhou, X Dai, Y Liang, R Paffenroth, D Korkin International Journal of Computational Biology and Drug Design 13 (1), 98-123, 2020 | 15 | 2020 |
| Robust Variational Autoencoders: Generating Noise-Free Images from Corrupted Images H Ren, Y Yue, C Zhou, RC Paffenroth, Y Li, ML Weiss | 3 | 2018 |
| A robust principal component analysis approach to DoS-related network anomaly detection C Doucette, R Broderick-Sander, B Toll, A Helsinger, N Soule, P Pal, ... Cyber Sensing 2020 11417, 47-58, 2020 | 2 | 2020 |
| Anomaly Detection via Graphical Lasso H Liu, RC Paffenroth, J Zou, C Zhou arXiv preprint arXiv:1811.04277, 2018 | 2 | 2018 |
| Robust auto-encoders C Zhou PhD Thesis, Worcester Institute, USA, 2016 | 1 | 2016 |
| Robust Methods for Anomaly Detection C Zhou Worcester Polytechnic Institute, 2019 | | 2019 |
Randy PaffenrothWorcester Polytechnic Institute在 wpi.edu 的电子邮件经过验证
