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Edward Raff
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Año
Malware Detection by Eating a Whole EXE
E Raff, J Barker, J Sylvester, R Brandon, B Catanzaro, C Nicholas
AAAI Workshop on Artificial Intelligence for Cyber Security, 2018
6462018
Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling
S Biderman, H Schoelkopf, Q Anthony, H Bradley, K O'Brien, E Hallahan, ...
International Conference on Machine Learning (ICML), 2023
4332023
Crosslingual Generalization through Multitask Finetuning
N Muennighoff, T Wang, L Sutawika, A Roberts, S Biderman, TL Scao, ...
Proceedings of the 61st Annual Meeting of the Association for Computational …, 2022
3802022
VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance
K Crowson, S Biderman, D Kornis, D Stander, E Hallahan, L Castricato, ...
European Conference on Computer Vision (ECCV), 2022
341*2022
An investigation of byte n-gram features for malware classification
E Raff, R Zak, R Cox, J Sylvester, P Yacci, R Ward, A Tracy, M McLean, ...
Journal of Computer Virology and Hacking Techniques, 1-20, 2016
1862016
Barrage of random transforms for adversarially robust defense
E Raff, J Sylvester, S Forsyth, M McLean
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
1752019
Learning the PE Header, Malware Detection with Minimal Domain Knowledge
E Raff, J Sylvester, C Nicholas
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security …, 2017
1622017
Exploratory analysis of covid-19 tweets using topic modeling, umap, and digraphs
C Ordun, S Purushotham, E Raff
epiDAMIK 2020: 3rd epiDAMIK ACM SIGKDD International Workshop on …, 2020
142*2020
Accounting for variance in machine learning benchmarks
X Bouthillier, P Delaunay, M Bronzi, A Trofimov, B Nichyporuk, J Szeto, ...
Proceedings of Machine Learning and Systems 3, 747-769, 2021
1302021
A Step Toward Quantifying Independently Reproducible Machine Learning Research
E Raff
Advances in Neural Information Processing Systems, 5485-5495, 2019
1252019
An Alternative to NCD for Large Sequences, Lempel-Ziv Jaccard Distance
E Raff, C Nicholas
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017
1002017
Fair Forests: Regularized Tree Induction to Minimize Model Bias
E Raff, J Sylvester, S Mills
AAAI/ACM Conference on AI, Ethics, and Society, 2017
782017
JSAT: Java Statistical Analysis Tool, a Library for Machine Learning
E Raff
Journal of Machine Learning Research 18 (23), 1-5, 2017
662017
Gradient Reversal Against Discrimination: A Fair Neural Network Learning Approach
E Raff, J Sylvester
The 5th IEEE International Conference on Data Science and Advanced Analytics, 2018
59*2018
A Survey of Machine Learning Methods and Challenges for Windows Malware Classification
E Raff, C Nicholas
NeurIPS 2020 Workshop: ML Retrospectives, Surveys & Meta-Analyses (ML-RSA), 2020
562020
Emergent and predictable memorization in large language models
S Biderman, US Prashanth, L Sutawika, H Schoelkopf, Q Anthony, ...
NeurIPS, 2023
552023
Static malware detection & subterfuge: Quantifying the robustness of machine learning and current anti-virus
W Fleshman, E Raff, R Zak, M McLean, C Nicholas
2018 13th International Conference on Malicious and Unwanted Software …, 2018
552018
Lempel-Ziv Jaccard Distance, an Effective Alternative to Ssdeep and Sdhash
E Raff, CK Nicholas
Digital Investigation, 2018
522018
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection
E Raff, W Fleshman, R Zak, HS Anderson, B Filar, M McLean
The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2021
492021
Malware Classification and Class Imbalance via Stochastic Hashed LZJD
E Raff, C Nicholas
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security …, 2017
472017
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Artículos 1–20