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ORCIDNathan M. VanHoudnos
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Conference and Workshop Papers
- 2024
[c3]Shannon K. Gallagher
, Jasmine Ratchford, Tyler Brooks, Bryan P. Brown, Eric Heim, William R. Nichols, Scott Mcmillan, Swati Rallapalli, Carol J. Smith, Nathan M. VanHoudnos, Nick Winski, Andrew O. Mellinger:
Assessing LLMs for High Stakes Applications. ICSE-SEIP 2024: 103-105- 2020
- [c2]Jonathan M. Spring, April Galyardt, Allen D. Householder, Nathan M. VanHoudnos:
On managing vulnerabilities in AI/ML systems. NSPW 2020: 111-126 - 2018
- [c1]Lori Flynn, William Snavely, David Svoboda, Nathan M. VanHoudnos, Richard Qin, Jennifer Burns, David Zubrow, Robert Stoddard, Guillermo Marce-Santurio:
Prioritizing alerts from multiple static analysis tools, using classification models. SQUADE@ICSE 2018: 13-20
Informal and Other Publications
- 2022
- [i4]Violet Turri, Rachel Dzombak, Eric Heim, Nathan M. VanHoudnos, Jay Palat, Anusha Sinha:
Measuring AI Systems Beyond Accuracy. CoRR abs/2204.04211 (2022) - 2021
- [i3]Jonathan Helland, Nathan M. VanHoudnos:
On the human-recognizability phenomenon of adversarially trained deep image classifiers. CoRR abs/2101.05219 (2021) - [i2]Jonathan M. Spring, April Galyardt, Allen D. Householder, Nathan M. VanHoudnos:
On managing vulnerabilities in AI/ML systems. CoRR abs/2101.10865 (2021) - 2018
- [i1]Carson D. Sestili, William S. Snavely, Nathan M. VanHoudnos:
Towards security defect prediction with AI. CoRR abs/1808.09897 (2018)
Coauthor Index
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