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ORCIDJohn T. Holodnak
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2020 – today
- 2024
[j4]Steven Jorgensen
, John T. Holodnak, Jensen Dempsey, Karla de Souza, Ananditha Raghunath, Vernon Rivet, Noah Demoes, Andrés Alejos, Allan B. Wollaber:
Extensible Machine Learning for Encrypted Network Traffic Application Labeling via Uncertainty Quantification. IEEE Trans. Artif. Intell. 5(1): 420-433 (2024)- [i6]Giorgio Severi, Simona Boboila, John T. Holodnak, Kendra Kratkiewicz, Rauf Izmailov, Alina Oprea:
Model-agnostic clean-label backdoor mitigation in cybersecurity environments. CoRR abs/2407.08159 (2024) - 2023
- [c6]Giorgio Severi, Simona Boboila, Alina Oprea, John T. Holodnak, Kendra Kratkiewicz, Jason Matterer:
Poisoning Network Flow Classifiers. ACSAC 2023: 337-351 - [c5]Harry X. Li, Steven Jorgensen, John T. Holodnak, Allan B. Wollaber:
ScatterUQ: Interactive Uncertainty Visualizations for Multiclass Deep Learning Problems. IEEE VIS (Short Papers) 2023: 246-250 - [i5]Giorgio Severi, Simona Boboila, Alina Oprea, John T. Holodnak, Kendra Kratkiewicz, Jason Matterer:
Poisoning Network Flow Classifiers. CoRR abs/2306.01655 (2023) - [i4]Harry X. Li, Steven Jorgensen, John T. Holodnak, Allan B. Wollaber:
ScatterUQ: Interactive Uncertainty Visualizations for Multiclass Deep Learning Problems. CoRR abs/2308.04588 (2023) - 2022
- [c4]Baolin Li, Rohin Arora, Siddharth Samsi, Tirthak Patel, William Arcand, David Bestor, Chansup Byun, Rohan Basu Roy, Bill Bergeron, John T. Holodnak, Michael Houle, Matthew Hubbell, Michael Jones, Jeremy Kepner, Anna Klein, Peter Michaleas, Joseph McDonald, Lauren Milechin, Julie Mullen, Andrew Prout, Benjamin Price, Albert Reuther, Antonio Rosa, Matthew L. Weiss, Charles Yee, Daniel Edelman, Allan Vanterpool, Anson Cheng, Vijay Gadepally, Devesh Tiwari:
AI-Enabling Workloads on Large-Scale GPU-Accelerated System: Characterization, Opportunities, and Implications. HPCA 2022: 1224-1237 - [c3]John T. Holodnak, Olivia M. Brown, Jason Matterer, Andrew Lemke:
Backdoor Poisoning of Encrypted Traffic Classifiers. ICDM (Workshops) 2022: 577-585 - [i3]Steven Jorgensen, John T. Holodnak, Jensen Dempsey, Karla de Souza, Ananditha Raghunath, Vernon Rivet, Noah Demoes, Andrés Alejos, Allan B. Wollaber:
Extensible Machine Learning for Encrypted Network Traffic Application Labeling via Uncertainty Quantification. CoRR abs/2205.05628 (2022) - 2021
- [i2]John T. Holodnak, Allan B. Wollaber:
On the Effectiveness of Mode Exploration in Bayesian Model Averaging for Neural Networks. CoRR abs/2112.03773 (2021)
2010 – 2019
- 2019
- [c2]Alexandra Clifford, Cassian Corey, John T. Holodnak:
An Empirical Evaluation of the Effect of Adversarial Labels on Classifier Accuracy Estimation. FLAIRS 2019: 2-7 - 2018
- [j3]John T. Holodnak, Ilse C. F. Ipsen, Ralph C. Smith:
A Probabilistic Subspace Bound with Application to Active Subspaces. SIAM J. Matrix Anal. Appl. 39(3): 1208-1220 (2018) - 2016
- [c1]Shannon C. Roberts, John T. Holodnak, Trang Nguyen, Sophia Yuditskaya, Maja Milosavljevic, William W. Streilein:
A Model-Based Approach to Predicting the Performance of Insider Threat Detection Systems. IEEE Symposium on Security and Privacy Workshops 2016: 314-323 - 2015
- [j2]John T. Holodnak, Ilse C. F. Ipsen:
Randomized Approximation of the Gram Matrix: Exact Computation and Probabilistic Bounds. SIAM J. Matrix Anal. Appl. 36(1): 110-137 (2015) - [j1]John T. Holodnak, Ilse C. F. Ipsen, Thomas Wentworth:
Conditioning of Leverage Scores and Computation by QR Decomposition. SIAM J. Matrix Anal. Appl. 36(3): 1143-1163 (2015) - 2013
- [i1]John T. Holodnak, Ilse C. F. Ipsen:
Randomized Matrix Multiplication: Exact Computation and Probabilistic Bounds. CoRR abs/1310.1502 (2013)
Coauthor Index
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