| The extreme value machine EM Rudd, LP Jain, WJ Scheirer, TE Boult IEEE transactions on pattern analysis and machine intelligence 40 (3), 762-768, 2017 | 380 | 2017 |
| Adversarial diversity and hard positive generation A Rozsa, EM Rudd, TE Boult Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 346 | 2016 |
| Moon: A mixed objective optimization network for the recognition of facial attributes EM Rudd, M Günther, TE Boult Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 262 | 2016 |
| A survey of stealth malware attacks, mitigation measures, and steps toward autonomous open world solutions EM Rudd, A Rozsa, M Günther, TE Boult IEEE Communications Surveys & Tutorials 19 (2), 1145-1172, 2016 | 200 | 2016 |
| SOREL-20M: A large scale benchmark dataset for malicious PE detection R Harang, EM Rudd arXiv preprint arXiv:2012.07634, 2020 | 108 | 2020 |
| Toward open-set face recognition M Gunther, S Cruz, EM Rudd, TE Boult Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 100 | 2017 |
| Facial attributes: Accuracy and adversarial robustness A Rozsa, M Günther, EM Rudd, TE Boult Pattern Recognition Letters 124, 100-108, 2019 | 71 | 2019 |
| Are facial attributes adversarially robust? A Rozsa, M Günther, EM Rudd, TE Boult 2016 23rd International Conference on Pattern Recognition (ICPR), 3121-3127, 2016 | 58 | 2016 |
| Incremental open set intrusion recognition using extreme value machine J Henrydoss, S Cruz, EM Rudd, M Gunther, TE Boult 2017 16th IEEE International Conference on Machine Learning and Applications …, 2017 | 51 | 2017 |
| Meade: Towards a malicious email attachment detection engine EM Rudd, R Harang, J Saxe 2018 IEEE International Symposium on Technologies for Homeland Security (HST …, 2018 | 45 | 2018 |
| Open set intrusion recognition for fine-grained attack categorization S Cruz, C Coleman, EM Rudd, TE Boult 2017 IEEE International Symposium on Technologies for Homeland Security (HST …, 2017 | 37 | 2017 |
| {ALOHA}: Auxiliary Loss Optimization for Hypothesis Augmentation EM Rudd, FN Ducau, C Wild, K Berlin, R Harang 28th USENIX Security Symposium (USENIX Security 19), 303-320, 2019 | 28 | 2019 |
| Exemplar codes for facial attributes and tattoo recognition MJ Wilber, E Rudd, B Heflin, YM Lui, TE Boult IEEE Winter Conference on Applications of Computer Vision, 205-212, 2014 | 24 | 2014 |
| Automated big text security classification K Alzhrani, EM Rudd, TE Boult, CE Chow 2016 IEEE Conference on Intelligence and Security Informatics (ISI), 103-108, 2016 | 23 | 2016 |
| Paraph: presentation attack rejection by analyzing polarization hypotheses EM Rudd, M Gunther, TE Boult Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 23 | 2016 |
| Automatic malware description via attribute tagging and similarity embedding FN Ducau, EM Rudd, TM Heppner, A Long, K Berlin arXiv preprint arXiv:1905.06262, 2019 | 19 | 2019 |
| Learning from context: A multi-view deep learning architecture for malware detection A Kyadige, EM Rudd, K Berlin 2020 IEEE Security and Privacy Workshops (SPW), 1-7, 2020 | 17 | 2020 |
| Automated us diplomatic cables security classification: Topic model pruning vs. classification based on clusters K Alzhrani, EM Rudd, CE Chow, TE Boult 2017 IEEE International Symposium on Technologies for Homeland Security (HST …, 2017 | 17 | 2017 |
| Automated big security text pruning and classification K Alzhrani, EM Rudd, CE Chow, TE Boult 2016 IEEE International Conference on Big Data (Big Data), 3629-3637, 2016 | 17 | 2016 |
| Learning from context: Exploiting and interpreting file path information for better malware detection A Kyadige, EM Rudd, K Berlin arXiv preprint arXiv:1905.06987, 2019 | 7 | 2019 |
Terrance E. BoultCU Distinguished El Pomar Prof. of Innovation and Security, University of Colorado Colorado SpringsDirección de correo verificada de vast.uccs.edu
