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ORCIDJaganmohan Chandrasekaran
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2020 – today
- 2024
[j1]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)- [c13]Krishna Khadka, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn:
A Combinatorial Approach to Hyperparameter Optimization. CAIN 2024: 140-149 - 2023
- [c12]Krishna Khadka, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn:
Synthetic Data Generation Using Combinatorial Testing and Variational Autoencoder. ICSTW 2023: 228-236 - [i2]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) - [i1]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) - 2022
- [c11]Sunny Shree, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn:
DeltaExplainer: A Software Debugging Approach to Generating Counterfactual Explanations. AITest 2022: 103-110 - [c10]Jaganmohan Chandrasekaran, Feras A. Batarseh, Laura J. Freeman, Raghu Kacker, M. S. Raunak, Rick Kuhn:
Enabling AI Adoption through Assurance. FLAIRS 2022 - [c9]Ankita Ramjibhai Patel, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, D. Richard Kuhn:
A Combinatorial Approach to Fairness Testing of Machine Learning Models. ICST Workshops 2022: 94-101 - 2021
- [c8]Jaganmohan Chandrasekaran, Ankita Ramjibhai Patel, Yu Lei, Raghu Kacker, D. Richard Kuhn:
Evaluation of T-Way Testing of DNNs in Autonomous Driving Systems. AITest 2021: 17-18 - [c7]Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn:
A Combinatorial Approach to Explaining Image Classifiers. ICST Workshops 2021: 35-43 - [c6]Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn:
A Combinatorial Approach to Testing Deep Neural Network-based Autonomous Driving Systems. ICST Workshops 2021: 57-66 - 2020
- [c5]Jaganmohan Chandrasekaran, Huadong Feng, Yu Lei, Raghu Kacker, D. Richard Kuhn:
Effectiveness of dataset reduction in testing machine learning algorithms. AITest 2020: 133-140
2010 – 2019
- 2018
- [c4]Huadong Feng, Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn:
A Method-Level Test Generation Framework for Debugging Big Data Applications. IEEE BigData 2018: 221-230 - 2017
- [c3]Jaganmohan Chandrasekaran, Huadong Feng, Yu Lei, D. Richard Kuhn, Raghu Kacker:
Applying Combinatorial Testing to Data Mining Algorithms. ICST Workshops 2017: 253-261 - 2016
- [c2]Jaganmohan Chandrasekaran, Laleh S. Ghandehari, Yu Lei, Raghu Kacker, D. Richard Kuhn:
Evaluating the Effectiveness of BEN in Localizing Different Types of Software Fault. ICST Workshops 2016: 26-34 - 2015
- [c1]Laleh Shikh Gholamhossein Ghandehari, Jaganmohan Chandrasekaran, Yu Lei, Raghu Kacker, D. Richard Kuhn:
BEN: A combinatorial testing-based fault localization tool. ICST Workshops 2015: 1-4
Coauthor Index
aka: Raghu N. Kacker
aka: Rick Kuhn
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