Underplating in the Himalaya-Tibet Collision Zone Revealed by the Hi-CLIMB Experiment J Nábělek, G Hetényi, J Vergne, S Sapkota, B Kafle, M Jiang, H Su, ... Science 325 (5946), 1371-1374, 2009 | 866 | 2009 |
Towards security defect prediction with AI CD Sestili, WS Snavely, NM VanHoudnos arXiv preprint arXiv:1808.09897, 2018 | 58 | 2018 |
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 | 31 | 2018 |
Markov chain Monte Carlo for item response models BW Junker, RJ Patz, NM VanHoudnos Handbook of item response theory 2, 271-312, 2016 | 30 | 2016 |
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 | 21 | 2020 |
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 | 19 | 2016 |
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 | 13 | 2017 |
Robust and Secure AI H Barmer, R Dzombak, M Gaston, E Heim, V Palat, F Redner, T Smith, ... Carnegie Mellon University, 2021 | 4 | 2021 |
On the human-recognizability phenomenon of adversarially trained deep image classifiers J Helland, N VanHoudnos arXiv preprint arXiv:2101.05219, 2020 | 4 | 2020 |
On the Hedges Correction for a t-Test NM VanHoudnos, JB Greenhouse Journal of Educational and Behavioral Statistics 41 (4), 392-419, 2016 | 4 | 2016 |
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 | 3 | 2011 |
Lessons Learned in Coordinated Disclosure for Artificial Intelligence and Machine Learning Systems A Householder, V Sarvepalli, J Havrilla, M Churilla, L Pons, S Lau, ... https://insights.sei.cmu.edu/library/lessons-learned-in-coordinated …, 2024 | 1 | 2024 |
A Retrospective in Engineering Large Language Models for National Security S Gallagher, T Brooks, W Nichols, A Mellinger, E Heim, B Brown, ... | 1 | 2023 |
Measuring AI Systems Beyond Accuracy V Turri, R Dzombak, E Heim, N VanHoudnos, J Palat, A Sinha arXiv preprint arXiv:2204.04211, 2022 | 1 | 2022 |
Counter AI: What Is It and What Can You Do About It? N VanHoudnos, C Smith, M Churilla, SH Lau, L McIlvenny, G Touhill | | 2024 |
Assessing LLMs for High Stakes Applications SK Gallagher, J Ratchford, T Brooks, BP Brown, E Heim, WR Nichols, ... Proceedings of the 46th International Conference on Software Engineering …, 2024 | | 2024 |
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 |
On Correcting a Significance Test for Model Misspecification1 N VanHoudnos | | 2013 |