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ORCIDLaura J. Freeman
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2020 – today
- 2024
[j15]D. Richard Kuhn
, M. S. Raunak, Raghu N. Kacker, Jaganmohan Chandrasekaran, Erin Lanus, Tyler Cody, Laura J. Freeman:
Assured Autonomy Through Combinatorial Methods. Computer 57(5): 86-90 (2024)- [c15]Erin Lanus, Brian Lee, Luis Pol, Daniel Sobien, Justin Kauffman, Laura J. Freeman:
Coverage for Identifying Critical Metadata in Machine Learning Operating Envelopes. ICSTW 2024: 217-226 - [i12]Zain ul Abdeen, Padmaksha Roy, Ahmad Al-Tawaha, Rouxi Jia, Laura J. Freeman, Peter A. Beling, Chen-Ching Liu, Alberto L. Sangiovanni-Vincentelli, Ming Jin:
Defense against Joint Poison and Evasion Attacks: A Case Study of DERMS. CoRR abs/2405.02989 (2024) - 2023
- [j14]Tyler Cody, Emma Meno, Peter A. Beling, Laura J. Freeman:
Whole Campaign Emulation with Reinforcement Learning for Cyber Test. IEEE Instrum. Meas. Mag. 26(5): 25-30 (2023) - [j13]Laura J. Freeman:
Review: Is design data collection still relevant in the big data era? With extensions to machine learning. Qual. Reliab. Eng. Int. 39(4): 1102-1106 (2023) - [c14]Tyler Cody, Laura J. Freeman:
Metric Learning Improves the Ability of Combinatorial Coverage Metrics to Anticipate Classification Error. ICSTW 2023: 206-213 - [i11]Sai Gurrapu, Ajay Kulkarni, Lifu Huang, Ismini Lourentzou, Laura J. Freeman, Feras A. Batarseh:
Rationalization for Explainable NLP: A Survey. CoRR abs/2301.08912 (2023) - [i10]Sai Prathyush Katragadda, Tyler Cody, Peter A. Beling, Laura J. Freeman:
Active Learning with Combinatorial Coverage. CoRR abs/2302.14567 (2023) - [i9]Tyler Cody, Laura J. Freeman:
Metric Learning Improves the Ability of Combinatorial Coverage Metrics to Anticipate Classification Error. CoRR abs/2302.14616 (2023) - [i8]Padmaksha Roy, Jaganmohan Chandrasekaran, Erin Lanus, Laura J. Freeman, Jeremy Werner:
A Survey of Data Security: Practices from Cybersecurity and Challenges of Machine Learning. CoRR abs/2310.04513 (2023) - [i7]Jaganmohan Chandrasekaran, Tyler Cody, Nicola McCarthy, Erin Lanus, Laura J. Freeman:
Test & Evaluation Best Practices for Machine Learning-Enabled Systems. CoRR abs/2310.06800 (2023) - [i6]Li Xu, Yili Hong, Eric P. Smith, David S. McLeod, Xinwei Deng, Laura J. Freeman:
Deep Neural Network Identification of Limnonectes Species and New Class Detection Using Image Data. CoRR abs/2311.08661 (2023) - 2022
- [j12]Laura J. Freeman, Feras A. Batarseh, D. Richard Kuhn, M. S. Raunak, Raghu N. Kacker:
The Path to a Consensus on Artificial Intelligence Assurance. Computer 55(3): 82-86 (2022) - [j11]Katherine Cauthen, Prashant Rai, Nicholas Hale, Laura J. Freeman, Jaideep Ray:
Detecting technological maturity from bibliometric patterns. Expert Syst. Appl. 201: 117177 (2022) - [j10]Daniel Sobien, Erik Higgins, Justin Krometis, Justin Kauffman, Laura J. Freeman:
Improving Deep Learning for Maritime Remote Sensing through Data Augmentation and Latent Space. Mach. Learn. Knowl. Extr. 4(3): 665-687 (2022) - [c13]Tyler Cody, Stephen C. Adams, Peter A. Beling, Laura J. Freeman:
On Valuing the Impact of Machine Learning Faults to Cyber-Physical Production Systems. COINS 2022: 1-6 - [c12]Jaganmohan Chandrasekaran, Feras A. Batarseh, Laura J. Freeman, Raghu Kacker, M. S. Raunak, Rick Kuhn:
Enabling AI Adoption through Assurance. FLAIRS 2022 - [c11]Wan-Yi Mao, Mehmet Yardimci, Minh Nguyen, Dan Sobien, Laura J. Freeman, Feras A. Batarseh, Abdul Rahman, Vinita Fordham:
Trustworthy AI Solutions for Cyberbiosecurity Challenges in Water Supply Systems. FLAIRS 2022 - [c10]Sai Prathyush Katragadda, Tyler Cody, Peter A. Beling, Laura J. Freeman:
Active Learning with Combinatorial Coverage. ICMLA 2022: 1129-1136 - [c9]Tyler Cody, Erin Lanus, Daniel D. Doyle, Laura J. Freeman:
Systematic Training and Testing for Machine Learning Using Combinatorial Interaction Testing. ICST Workshops 2022: 102-109 - [i5]Tyler Cody, Erin Lanus, Daniel D. Doyle, Laura J. Freeman:
Systematic Training and Testing for Machine Learning Using Combinatorial Interaction Testing. CoRR abs/2201.12428 (2022) - 2021
- [j9]Feras A. Batarseh, Laura J. Freeman, Chih-Hao Huang:
A survey on artificial intelligence assurance. J. Big Data 8(1): 1-30 (2021) - [j8]Jingwei Huang, Peter A. Beling, Laura J. Freeman, Yong Zeng:
Trustworthy AI for Digital Engineering Transformation. J. Integr. Des. Process. Sci. 25(1): 1-7 (2021) - [j7]Thomas H. Johnson, John T. Haman, Heather Wojton, Laura J. Freeman:
Circular prediction regions for miss distance models under heteroskedasticity. Qual. Reliab. Eng. Int. 37(7): 2991-3003 (2021) - [c8]Sami Wood, Erin Lanus, Daniel D. Doyle, Jeremy Ogorzalek, Christopher T. Franck, Laura J. Freeman:
Developing Hierarchies for Image Classification Model Evaluation. AI4I 2021: 34-37 - [c7]Feras A. Batarseh, Dominick Perini, Qasim Wani, Laura J. Freeman:
Explainable Artificial Intelligence for Technology Policy Making Using Attribution Networks. AI*IA 2021: 624-637 - [c6]Anderson Monken, Flora Haberkorn, Munisamy Gopinath, Laura J. Freeman, Feras A. Batarseh:
Graph Neural Networks for Modeling Causality in International Trade. FLAIRS 2021 - [c5]Sayyed Farid Ahamed, Priyanka Aggarwal, Sachin Shetty, Erin Lanus, Laura J. Freeman:
ATTL: An Automated Targeted Transfer Learning with Deep Neural Networks. GLOBECOM 2021: 1-7 - [c4]Erin Lanus, Laura J. Freeman, D. Richard Kuhn, Raghu N. Kacker:
Combinatorial Testing Metrics for Machine Learning. ICST Workshops 2021: 81-84 - [c3]Erin Lanus, Ivan Hernandez, Adam Dachowicz, Laura J. Freeman, Melanie Grande, Andrew Lang, Jitesh H. Panchal, Anthony Patrick, Scott Welch:
Test and Evaluation Framework for Multi-Agent Systems of Autonomous Intelligent Agents. SOSE 2021: 203-209 - [c2]Priyanka Aggarwal, Sayyed Farid Ahamed, Sachin Shetty, Laura J. Freeman:
Selective Targeted Transfer Learning for Malware Classification. TPS-ISA 2021: 114-120 - [i4]Erin Lanus, Ivan Hernandez, Adam Dachowicz, Laura J. Freeman, Melanie Grande, Andrew Lang, Jitesh H. Panchal, Anthony Patrick, Scott Welch:
Test and Evaluation Framework for Multi-Agent Systems of Autonomous Intelligent Agents. CoRR abs/2101.10430 (2021) - [i3]Yili Hong, Jiayi Lian, Li Xu, Jie Min, Yueyao Wang, Laura J. Freeman, Xinwei Deng:
Statistical Perspectives on Reliability of Artificial Intelligence Systems. CoRR abs/2111.05391 (2021) - [i2]Feras A. Batarseh, Laura J. Freeman:
A Survey on AI Assurance. CoRR abs/2111.07505 (2021) - 2020
- [i1]Jiayi Lian, Laura J. Freeman, Yili Hong, Xinwei Deng:
Investigating the Robustness of Artificial Intelligent Algorithms with Mixture Experiments. CoRR abs/2010.15551 (2020)
2010 – 2019
- 2019
- [j6]Laura J. Freeman:
Special Issue: Advancing Statistical Methods for Testing and Evaluating Defense Systems. Qual. Reliab. Eng. Int. 35(3): 737 (2019) - [j5]Rebecca M. Medlin, Laura J. Freeman, Jennifer L. K. Kensler, G. Geoffrey Vining:
Analysis of split-plot reliability experiments with subsampling. Qual. Reliab. Eng. Int. 35(3): 738-749 (2019) - [j4]Thomas H. Johnson, Rebecca M. Medlin, Laura J. Freeman:
Power approximations for failure-time regression models. Qual. Reliab. Eng. Int. 35(6): 1666-1675 (2019) - 2016
- [j3]Matthew Avery, Mark Orndorff, Timothy J. Robinson, Laura J. Freeman:
Regularization for Continuously Observed Ordinal Response Variables with Piecewise-constant Functional Covariates. Qual. Reliab. Eng. Int. 32(6): 2033-2042 (2016) - 2014
- [j2]Thomas H. Johnson, Laura J. Freeman, Janice Hester, Jonathan L. Bell:
A Comparison of Ballistic Resistance Testing Techniques in the Department of Defense. IEEE Access 2: 1442-1455 (2014) - 2013
- [j1]Laura J. Freeman, G. Geoffrey Vining:
Reliability Data Analysis for Life Test Designed Experiments with Sub-Sampling. Qual. Reliab. Eng. Int. 29(4): 509-519 (2013) - [c1]Vivek K. Singh, Laura J. Freeman, Bruno Lepri, Alex Pentland:
Predicting Spending Behavior Using Socio-mobile Features. SocialCom 2013: 174-179
Coauthor Index
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