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Nathan VanHoudnos
Nathan VanHoudnos
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Towards security defect prediction with AI
CD Sestili, WS Snavely, NM VanHoudnos
arXiv preprint arXiv:1808.09897, 2018
432018
Prioritizing alerts from multiple static analysis tools, using classification models
L Flynn, W Snavely, D Svoboda, N VanHoudnos, R Qin, J Burns, ...
Proceedings of the 1st international workshop on software qualities and …, 2018
292018
Markov chain Monte Carlo for item response models
BW Junker, RJ Patz, NM VanHoudnos
Handbook of item response theory 2, 271-312, 2016
292016
The critical role of positive incentives for reducing insider threats
AP Moore, SJ Perl, J Cowley, ML Collins, TM Cassidy, N VanHoudnos, ...
SEI Technical Report CMU/SEI-2016-TR-014, 2016
172016
On managing vulnerabilities in AI/ML systems
JM Spring, A Galyardt, AD Householder, N VanHoudnos
Proceedings of the New Security Paradigms Workshop 2020, 111-126, 2020
152020
This malware looks familiar: Laymen identify malware run-time similarity with chernoff faces and stick figures
N VanHoudnos, W Casey, D French, B Lindauer, E Kanal, E Wright, ...
10th EAI International Conference on Bio-inspired Information and …, 2017
112017
Towards security defect prediction with AI (2018)
CD Sestili, WS Snavely, NM VanHoudnos
arXiv preprint arXiv:1808.09897, 0
5
On the human-recognizability phenomenon of adversarially trained deep image classifiers
J Helland, N VanHoudnos
arXiv preprint arXiv:2101.05219, 2020
42020
On the Hedges Correction for a t-Test
NM VanHoudnos, JB Greenhouse
Journal of Educational and Behavioral Statistics 41 (4), 392-419, 2016
42016
Robust and Secure AI
H Barmer, R Dzombak, M Gaston, E Heim, V Palat, F Redner, T Smith, ...
Carnegie Mellon University, 2021
32021
Can the internet grade math? crowdsourcing a complex scoring task and picking the optimal crowd size
N Van Houdnos
Dietrich College of Humanities and Social Sciences at Research Showcase@ CMU, 2011
32011
Measuring AI Systems Beyond Accuracy
V Turri, R Dzombak, E Heim, N VanHoudnos, J Palat, A Sinha
arXiv preprint arXiv:2204.04211, 2022
12022
A Retrospective in Engineering Large Language Models for National Security
S Gallagher, T Brooks, W Nichols, A Mellinger, E Heim, B Brown, ...
2023
COMMENTS ON NIST AI RMF RFI
R Dzombak, R Krishnan, C Smith, B Tucker, N VanHoudnos, ...
2021
Adversarial Machine Learning for the DoD
N VanHoudnos
2020
Train, but Verify: Towards Practical AI Robustness
N VanHoudnos, O Wright, AF Fredrickson, K Leino, B Parno
2020
Human-Computer Decision Systems for Cybersecurity
N VanHoudnos, S Moon, D French, B Lindauer, P Jansen, J Carbonell, ...
2016
General Framework for Effect Sizes in Cluster Randomized Experiments.
N VanHoudnos
Society for Research on Educational Effectiveness, 2016
2016
The Efficacy of the Hedges Correction for Unmodeled Clustering, and Its Generalizations in Practical Settings A Dissertation Submitted to the Graduate School in Partial …
N VanHoudnos
Carnegie Mellon University Pittsburgh, 2014
2014
The efficacy of the Hedges correction for unmodeled clustering, and its generalizations in practical settings
N VanHoudnos
Carnegie Mellon University, 2014
2014
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