Joseph, Anthony D.
University of California, Berkeley
6 papers on CoChatORCID 0000-0002-6798-9664
Most cited papers
- Verified
A view of cloud computing
Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., et al. (2010) · Communications of the ACM
Cloud Computing and Resource ManagementCloud Data Security Solutions
Cited by 9,464
- Verified
Toil enables reproducible, open source, big biomedical data analyses
Vivian, J., Rao, A. A., Nothaft, F. A., Ketchum, C., Armstrong, J., Novak, A., Pfeil, J., Narkizian, J., Deran, A. D., Musselman-Brown, A., et al. (2017) · Nature Biotechnology
Scientific Computing and Data ManagementGenomics and Phylogenetic Studies
Cited by 1,365
- Verified
Adversarial machine learning
Huang, L., Joseph, A. D., Nelson, B., Rubinstein, B. I. P., & Tygar, J. D. (2011) · Proceedings of the 4th ACM workshop on Security and artificial intelligence
Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data
Cited by 1,194
- Verified
A Taxonomy of Cyber Attacks on SCADA Systems
Zhu, B., Joseph, A., & Sastry, S. (2011) · 2011 International Conference on Internet of Things and 4th International Conference on Cyber, Physical and Social Computing
Smart Grid Security and ResilienceInformation and Cyber Security
Cited by 458
- Verified
ANTIDOTE: understanding and defending against poisoning of anomaly detectors
Rubinstein, B. I. P., Nelson, B., Huang, L., Joseph, A. D., Lau, S.-H., Rao, S., Taft, N., & Tygar, J. D. (2009) · Proceedings of the 9th ACM SIGCOMM conference on Internet measurement
Adversarial Robustness in Machine LearningNetwork Security and Intrusion Detection
Cited by 331
- Verified
A Berkeley View of Systems Challenges for AI
Stoica, I., Song, D., Popa, R. A., Patterson, D., Mahoney, M. W., Katz, R., Joseph, A. D., Jordan, M., Hellerstein, J. M., Gonzalez, J. E., et al. (2017) · arXiv
Artificial Intelligence ApplicationsAdvanced Neural Network Applications
Cited by 171
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