| 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 | 118 | 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 | 81 | 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 | 43 | 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 | 33 | 2020 |
| 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 | 20 | 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 | 17 | 2021 |
| 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 | 13 | 2022 |
| 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 | 5 | 2023 |
| 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 | 5 | 2022 |
| 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 | 4 | 2020 |
| A coreset learning reality check F Lu, E Raff, J Holt Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8940-8948, 2023 | 3 | 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 | 3 | 2022 |
| Exploring the sharpened cosine similarity S Wu, F Lu, E Raff, J Holt arXiv preprint arXiv:2307.13855, 2023 | 2 | 2023 |
| Lempel-Ziv Networks R Saul, MM Alam, J Hurwitz, E Raff, T Oates, J Holt Proceedings on, 1-11, 2023 | 2 | 2023 |
| 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 | 1 | 2024 |
| Minimizing Compute Costs: When Should We Run More Expensive Malware Analysis? AT Nguyen, R Zak, LE Richards, M Fuchs, F Lu, R Brandon, GL Munoz, ... | 1 | 2022 |
| RelExt A Pingle, A Piplai, S Mittal, A Joshi, J Holt, R Zak Proceedings of the 2019 IEEE/ACM International Conference on Advances in …, 2019 | 1 | 2019 |
| 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 | | 2024 |
| Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection M Mahmudul Alam, E Raff, S Biderman, T Oates, J Holt arXiv e-prints, arXiv: 2403.17978, 2024 | | 2024 |
| Reproducibility in Multiple Instance Learning: A Case For Algorithmic Unit Tests E Raff, J Holt Advances in Neural Information Processing Systems 36, 2024 | | 2024 |
Edward RaffBooz Allen Hamilton, UMBCAdresse e-mail validée de bah.com
