| Relext: Relation extraction using deep learning approaches for cybersecurity knowledge graph improvement A Pingle, A Piplai, S Mittal, A Joshi, J Holt, R Zak Proceedings of the 2019 IEEE/ACM International Conference on Advances in …, 2019 | 152 | 2019 |
| Creating cybersecurity knowledge graphs from malware after action reports A Piplai, S Mittal, A Joshi, T Finin, J Holt, R Zak IEEE Access 8, 211691-211703, 2020 | 118 | 2020 |
| Grand challenge: Applying artificial intelligence and machine learning to cybersecurity K Bresniker, A Gavrilovska, J Holt, D Milojicic, T Tran Computer 52 (12), 45-52, 2019 | 68 | 2019 |
| Automatic yara rule generation using biclustering E Raff, R Zak, G Lopez Munoz, W Fleming, HS Anderson, B Filar, ... Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security …, 2020 | 47 | 2020 |
| Out of distribution data detection using dropout bayesian neural networks AT Nguyen, F Lu, GL Munoz, E Raff, C Nicholas, J Holt Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7877-7885, 2022 | 30 | 2022 |
| Learning with holographic reduced representations A Ganesan, H Gao, S Gandhi, E Raff, T Oates, J Holt, M McLean Advances in neural information processing systems 34, 25606-25620, 2021 | 29 | 2021 |
| Leveraging uncertainty for improved static malware detection under extreme false positive constraints AT Nguyen, E Raff, C Nicholas, J Holt arXiv preprint arXiv:2108.04081, 2021 | 24 | 2021 |
| Recasting self-attention with holographic reduced representations MM Alam, E Raff, S Biderman, T Oates, J Holt International Conference on Machine Learning, 490-507, 2023 | 12 | 2023 |
| Getting passive aggressive about false positives: patching deployed malware detectors E Raff, B Filar, J Holt 2020 International Conference on Data Mining Workshops (ICDMW), 506-515, 2020 | 9 | 2020 |
| Efficient malware analysis using metric embeddings EM Rudd, D Krisiloff, S Coull, D Olszewski, E Raff, J Holt Digital Threats: Research and Practice 5 (1), 1-20, 2024 | 8 | 2024 |
| Deploying convolutional networks on untrusted platforms using 2D holographic reduced representations MM Alam, E Raff, T Oates, J Holt arXiv preprint arXiv:2206.05893, 2022 | 7 | 2022 |
| Reproducibility in multiple instance learning: a case for algorithmic unit tests E Raff, J Holt Advances in Neural Information Processing Systems 36, 13530-13544, 2023 | 6 | 2023 |
| A coreset learning reality check F Lu, E Raff, J Holt Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8940-8948, 2023 | 6 | 2023 |
| Holographic global convolutional networks for long-range prediction tasks in malware detection MM Alam, E Raff, SR Biderman, T Oates, J Holt International Conference on Artificial Intelligence and Statistics, 4042-4050, 2024 | 5 | 2024 |
| Small Effect Sizes in Malware Detection? Make Harder Train/Test Splits! T Patel, F Lu, E Raff, C Nicholas, C Matuszek, J Holt arXiv preprint arXiv:2312.15813, 2023 | 5 | 2023 |
| Lempel-ziv networks R Saul, MM Alam, J Hurwitz, E Raff, T Oates, J Holt Proceedings on, 1-11, 2023 | 5 | 2023 |
| Maldict: Benchmark datasets on malware behaviors, platforms, exploitation, and packers RJ Joyce, E Raff, C Nicholas, J Holt arXiv preprint arXiv:2310.11706, 2023 | 4 | 2023 |
| Marvolo: Programmatic data augmentation for practical ml-driven malware detection MD Wong, E Raff, J Holt, R Netravali arXiv preprint arXiv:2206.03265, 2022 | 4 | 2022 |
| Is Function Similarity Over-Engineered? Building a Benchmark R Saul, C Liu, N Fleischmann, R Zak, K Micinski, E Raff, J Holt arXiv preprint arXiv:2410.22677, 2024 | 3 | 2024 |
| Assemblage: Automatic Binary Dataset Construction for Machine Learning C Liu, R Saul, Y Sun, E Raff, M Fuchs, TS Pantano, J Holt, K Micinski arXiv preprint arXiv:2405.03991, 2024 | 3 | 2024 |
Edward RaffBooz Allen Hamilton, UMBCCorreu electrònic verificat a bah.com
