Recent Publications
A comprehensive list of publications, including preprints, can be found on Google Scholar and DBLP. Keynote Addresses, research talks, and interviews can be found on YouTube.
2024
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Hemberg, E., Turner, M. J., Rutar, N., & O’Reilly, U.-M. (2024). Enhancements to Threat, Vulnerability, and Mitigation Knowledge for
Cyber Analytics, Hunting, and Simulations. DTRAP, 5(1), 8:1–8:33. https://doi.org/10.1145/3615668
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Hemberg, E., Moskal, S., & O’Reilly, U.-M. (2024). Evolving code with a large language model. Genet. Program. Evolvable Mach., 25(2), 21. https://doi.org/10.1007/S10710-024-09494-2
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Fajardo, M. A. H., Hemberg, E., Toutouh, J., O’Reilly, U.-M., & Lehre, P. K. (2024). A Self-adaptive Coevolutionary Algorithm. In X. Li & J. Handl (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference,
GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024. ACM. https://doi.org/10.1145/3638529.3654132
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Hemberg, E., O’Reilly, U.-M., & Toutouh, J. (2024). Cooperative Coevolutionary Spatial Topologies for Autoencoder Training. In X. Li & J. Handl (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference,
GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024. ACM. https://doi.org/10.1145/3638529.3654127
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Jorgensen, S., Nadizar, G., Pietropolli, G., Manzoni, L., Medvet, E., O’Reilly, U.-M., & Hemberg, E. (2024). Large Language Model-based Test Case Generation for GP Agents. In X. Li & J. Handl (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference,
GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024. ACM. https://doi.org/10.1145/3638529.3654056
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O’Reilly, U.-M. (2024). Coevolution in Natural and Artificial Systems. In X. Li & J. Handl (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference,
GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024. ACM. https://doi.org/10.1145/3638529.3663651
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O’Reilly, U.-M., & Hemberg, E. (2024). Using Large Language Models for Evolutionary Search. In X. Li & J. Handl (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference
Companion, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024 (pp. 973–983). ACM. https://doi.org/10.1145/3638530.3648432
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Toutouh, J., & O’Reilly, U.-M. (2024). Coevolutionary Computation for Adversarial Deep Learning. In X. Li & J. Handl (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference
Companion, GECCO 2024, Melbourne, VIC, Australia, July 14-18, 2024 (pp. 1410–1431). ACM. https://doi.org/10.1145/3638530.3648405
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Hemberg, E., Moskal, S., & O’Reilly, U.-M. (2024). Evolving Code with A Large Language Model. CoRR, abs/2401.07102. https://doi.org/10.48550/ARXIV.2401.07102
2023
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Toutouh, J., Nalluru, S., Hemberg, E., & O’Reilly, U.-M. (2023). Semi-supervised generative adversarial networks with spatial coevolution
for enhanced image generation and classification. Appl. Soft Comput., 148, 110890. https://doi.org/10.1016/J.ASOC.2023.110890
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Shashkov, A., Hemberg, E., Tulla, M., & O’Reilly, U.-M. (2023). Adversarial agent-learning for cybersecurity: a comparison of algorithms. Knowl. Eng. Rev., 38, e3. https://doi.org/10.1017/S0269888923000012
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Gold, R., Branquinho, H., Hemberg, E., O’Reilly, U.-M., & Garcı́a-Sánchez Pablo. (2023). Genetic Programming and Coevolution to Play the Bomberman™
Video Game. In J. Correia, S. L. Smith, & R. Qaddoura (Eds.), Applications of Evolutionary Computation - 26th European Conference,
EvoApplications 2023, Held as Part of EvoStar 2023, Brno, Czech Republic,
April 12-14, 2023, Proceedings (Vol. 13989, pp. 765–779). Springer. https://doi.org/10.1007/978-3-031-30229-9_49
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Toutouh, J., Nalluru, S., Hemberg, E., & O’Reilly, U.-M. (2023). Semi-Supervised Learning with Coevolutionary Generative Adversarial
Networks. In S. Silva & Paquete Luı́s (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference,
GECCO 2023, Lisbon, Portugal, July 15-19, 2023 (pp. 568–576). ACM. https://doi.org/10.1145/3583131.3590426
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O’Reilly, U.-M., & Hemberg, E. (2023). Genetic Programming: A Tutorial Introduction. In S. Silva & Paquete Luı́s (Eds.), Companion Proceedings of the Conference on Genetic and Evolutionary
Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July
15-19, 2023 (pp. 1026–1036). ACM. https://doi.org/10.1145/3583133.3595061
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Lehre, P. K., Fajardo, M. A. H., Toutouh, J., Hemberg, E., & O’Reilly, U.-M. (2023). Analysis of a Pairwise Dominance Coevolutionary Algorithm And DefendIt. In S. Silva & Paquete Luı́s (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference,
GECCO 2023, Lisbon, Portugal, July 15-19, 2023 (pp. 1027–1035). ACM. https://doi.org/10.1145/3583131.3590411
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Toutouh, J., & O’Reilly, U.-M. (2023). Coevolutionary Computation for Adversarial Deep Learning. In S. Silva & Paquete Luı́s (Eds.), Companion Proceedings of the Conference on Genetic and Evolutionary
Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July
15-19, 2023 (pp. 1379–1398). ACM. https://doi.org/10.1145/3583133.3595049
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Fajardo, M. A. H., Lehre, P. K., Toutouh, J., Hemberg, E., & O’Reilly, U.-M. (2023). Analysis of a Pairwise Dominance Coevolutionary Algorithm with Spatial
Topology. In S. Winkler, L. Trujillo, C. Ofria, & T. Hu (Eds.), Genetic Programming Theory and Practice XX [GPTP 2023] (pp. 19–44). Springer. https://doi.org/10.1007/978-981-99-8413-8_2
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Kong, B. J., Hemberg, E., Bell, A., & O’Reilly, U.-M. (2023). Investigating Student’s Problem-solving Approaches in MOOCs using
Natural Language Processing. LAK 2023: 13th International Learning Analytics and Knowledge Conference,
LAK2023, Arlington, TX, USA, March 13-17, 2023, 262–272. https://doi.org/10.1145/3576050.3576091
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Wang, M., Srikant, S., Samak, M., & O’Reilly, U.-M. (2023). RaceInjector: Injecting Races to Evaluate and Learn Dynamic Race Detection
Algorithms. In P. Ferrara & L. Hadarean (Eds.), Proceedings of the 12th ACM SIGPLAN International Workshop on
the State Of the Art in Program Analysis, SOAP 2023, Orlando, FL,
USA, 17 June 2023 (pp. 63–70). ACM. https://doi.org/10.1145/3589250.3596142
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Jia, J., Srikant, S., Mitrovska, T., Gan, C., Chang, S., Liu, S., & O’Reilly, U.-M. (2023). ClawSAT: Towards Both Robust and Accurate Code Models. In T. Zhang, X. Xia, & N. Novielli (Eds.), IEEE International Conference on Software Analysis, Evolution and
Reengineering, SANER 2023, Taipa, Macao, March 21-24, 2023 (pp. 212–223). IEEE. https://doi.org/10.1109/SANER56733.2023.00029
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Srikant, S., Ivanova, A. A., Sueoka, Y., Kean, H. H., Dhamala, R., Fedorenko, E., Bers, M. U., & O’Reilly, U.-M. (2023). Program Comprehension Does Not Primarily Rely On the Language Centers
of the Human Brain. CoRR, abs/2304.12373. https://doi.org/10.48550/ARXIV.2304.12373
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Sankaranarayanan, A., Hemberg, E., & O’Reilly, U.-M. (2023). The Facebook Algorithm’s Active Role in Climate Advertisement Delivery. CoRR, abs/2308.03191. https://doi.org/10.48550/ARXIV.2308.03191
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Moskal, S., Laney, S., Hemberg, E., & O’Reilly, U.-M. (2023). LLMs Killed the Script Kiddie: How Agents Supported by Large Language
Models Change the Landscape of Network Threat Testing. CoRR, abs/2310.06936. https://doi.org/10.48550/ARXIV.2310.06936
2022
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Özlem Özmen Garibay, Yousefi, N., Aslett, K., Baggio, J. A., Hemberg, E., Jayalath, C., Mantzaris, A. V., Miller, B., O’Reilly, U.-M., Rand, W., Senevirathna, C., & Garibay, I. (2022). Entropy-Based Characterization of Influence Pathways in Traditional
and Social Media. 8th IEEE International Conference on Collaboration and Internet
Computing, CIC 2022, Atlanta, GA, USA, December 14-16, 2022, 38–44. https://doi.org/10.1109/CIC56439.2022.00016
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Tseng, S., Hemberg, E., & O’Reilly, U.-M. (2022). Synthesizing Programs from Program Pieces Using Genetic Programming
and Refinement Type Checking. In E. Medvet, G. L. Pappa, & B. Xue (Eds.), Genetic Programming - 25th European Conference, EuroGP 2022, Held
as Part of EvoStar 2022, Madrid, Spain, April 20-22, 2022, Proceedings (Vol. 13223, pp. 197–211). Springer. https://doi.org/10.1007/978-3-031-02056-8_13
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Schweim, D., Hemberg, E., Sobania, D., & O’Reilly, U.-M. (2022). Exploiting Knowledge from Code to Guide Program Search. In E. Medvet, G. L. Pappa, & B. Xue (Eds.), Genetic Programming - 25th European Conference, EuroGP 2022, Held
as Part of EvoStar 2022, Madrid, Spain, April 20-22, 2022, Proceedings (Vol. 13223, pp. 262–277). Springer. https://doi.org/10.1007/978-3-031-02056-8_17
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Flores, D., Hemberg, E., Toutouh, J., & O’Reilly, U.-M. (2022). Coevolutionary generative adversarial networks for medical image augumentation
at scale. In J. E. Fieldsend & M. Wagner (Eds.), GECCO ’22: Genetic and Evolutionary Computation Conference, Boston,
Massachusetts, USA, July 9 - 13, 2022 (pp. 367–376). ACM. https://doi.org/10.1145/3512290.3528742
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Zhao, Y., Hemberg, E., Derbinsky, N., Mata, G., & O’Reilly, U.-M. (2022). Using domain knowledge in coevolution and reinforcement learning to
simulate a logistics enterprise. In J. E. Fieldsend & M. Wagner (Eds.), GECCO ’22: Genetic and Evolutionary Computation Conference, Companion
Volume, Boston, Massachusetts, USA, July 9 - 13, 2022 (pp. 514–517). ACM. https://doi.org/10.1145/3520304.3528990
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Turner, M. J., Hemberg, E., & O’Reilly, U.-M. (2022). Analyzing multi-agent reinforcement learning and coevolution in cybersecurity. In J. E. Fieldsend & M. Wagner (Eds.), GECCO ’22: Genetic and Evolutionary Computation Conference, Boston,
Massachusetts, USA, July 9 - 13, 2022 (pp. 1290–1298). ACM. https://doi.org/10.1145/3512290.3528844
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Toutouh, J., & O’Reilly, U.-M. (2022). Coevolutionary computation for adversarial deep learning. In J. E. Fieldsend & M. Wagner (Eds.), GECCO ’22: Genetic and Evolutionary Computation Conference, Companion
Volume, Boston, Massachusetts, USA, July 9 - 13, 2022 (pp. 1487–1505). ACM. https://doi.org/10.1145/3520304.3533651
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Moskal, S., Hemberg, E., & O’Reilly, U.-M. (2022). CyberEvo: evolutionary search of knowledge-based behaviors in a cyber
attack campaign. In J. E. Fieldsend & M. Wagner (Eds.), GECCO ’22: Genetic and Evolutionary Computation Conference, Companion
Volume, Boston, Massachusetts, USA, July 9 - 13, 2022 (pp. 2168–2176). ACM. https://doi.org/10.1145/3520304.3533999
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Gold, R., Grant, A. H., Hemberg, E., Gunaratne, C., & O’Reilly, U.-M. (2022). GUI-based, efficient genetic programming for Unity3D. In J. E. Fieldsend & M. Wagner (Eds.), GECCO ’22: Genetic and Evolutionary Computation Conference, Companion
Volume, Boston, Massachusetts, USA, July 9 - 13, 2022 (pp. 2310–2313). ACM. https://doi.org/10.1145/3520304.3534022
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Gold, R., Grant, A. H., Hemberg, E., Gunaratne, C., & O’Reilly, U.-M. (2022). GUI-Based, Efficient Genetic Programming and AI Planning for Unity3D. In L. Trujillo, S. M. Winkler, S. Silva, & W. Banzhaf (Eds.), Genetic Programming Theory and Practice XIX [GPTP 2022] (pp. 57–79). Springer. https://doi.org/10.1007/978-981-19-8460-0_3
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Kim, J., O’Reilly, U.-M., & Seok, J. (2022). Computer Code Representation through Natural Language Processing for
fMRI Data Analysis. 2022 International Conference on Artificial Intelligence in Information
and Communication, ICAIIC 2022, Jeju Island, Korea, Republic of,
February 21-24, 2022, 184–187. https://doi.org/10.1109/ICAIIC54071.2022.9722644
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Srikant, S., Lipkin, B., Ivanova, A. A., Fedorenko, E., & O’Reilly, U.-M. (2022). Convergent Representations of Computer Programs in Human and Artificial
Neural Networks. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), Advances in Neural Information Processing Systems 35: Annual Conference
on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans,
LA, USA, November 28 - December 9, 2022. http://papers.nips.cc/paper_files/paper/2022/hash/77b5aaf2826c95c98e5eb4ab830073de-Abstract-Conference.html
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Jia, J., Srikant, S., Mitrovska, T., Gan, C., Chang, S., Liu, S., & O’Reilly, U.-M. (2022). CLAWSAT: Towards Both Robust and Accurate Code Models. CoRR, abs/2211.11711. https://doi.org/10.48550/ARXIV.2211.11711
2021
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Hemberg, E., Toutouh, J., Al-Dujaili, A., Schmiedlechner, T., & O’Reilly, U.-M. (2021). Spatial Coevolution for Generative Adversarial Network Training. ACM Trans. Evol. Learn. Optim., 1(2), 6:1–6:28. https://doi.org/10.1145/3458845
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Wick, J., Hemberg, E., & O’Reilly, U.-M. (2021). Getting a Head Start on Program Synthesis with Genetic Programming. In T. Hu, N. Lourenço, & E. Medvet (Eds.), Genetic Programming - 24th European Conference, EuroGP 2021, Held
as Part of EvoStar 2021, Virtual Event, April 7-9, 2021, Proceedings (Vol. 12691, pp. 263–279). Springer. https://doi.org/10.1007/978-3-030-72812-0_17
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Schweim, D., Hemberg, E., Sobania, D., O’Reilly, U.-M., & Rothlauf, F. (2021). Using knowledge of human-generated code to bias the search in program
synthesis with grammatical evolution. In K. Krawiec (Ed.), GECCO ’21: Genetic and Evolutionary Computation Conference, Companion
Volume, Lille, France, July 10-14, 2021 (pp. 331–332). ACM. https://doi.org/10.1145/3449726.3459548
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Toutouh, J., & O’Reilly, U.-M. (2021). Signal propagation in a gradient-based and evolutionary learning system. In F. Chicano & K. Krawiec (Eds.), GECCO ’21: Genetic and Evolutionary Computation Conference, Lille,
France, July 10-14, 2021 (pp. 377–385). ACM. https://doi.org/10.1145/3449639.3459319
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O’Reilly, U.-M., & Hemberg, E. (2021). Genetic programming: a tutorial introduction. In K. Krawiec (Ed.), GECCO ’21: Genetic and Evolutionary Computation Conference, Companion
Volume, Lille, France, July 10-14, 2021 (pp. 443–453). ACM. https://doi.org/10.1145/3449726.3461394
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Shlapentokh-Rothman, M., Kelly, J., Baral, A., Hemberg, E., & O’Reilly, U.-M. (2021). Coevolutionary modeling of cyber attack patterns and mitigations using
public datasets. In F. Chicano & K. Krawiec (Eds.), GECCO ’21: Genetic and Evolutionary Computation Conference, Lille,
France, July 10-14, 2021 (pp. 714–722). ACM. https://doi.org/10.1145/3449639.3459351
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Toutouh, J., & O’Reilly, U.-M. (2021). Coevolutionary computation for adversarial deep learning. In K. Krawiec (Ed.), GECCO ’21: Genetic and Evolutionary Computation Conference, Companion
Volume, Lille, France, July 10-14, 2021 (pp. 983–1001). ACM. https://doi.org/10.1145/3449726.3461419
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Zhao, Y., Hemberg, E., Derbinsky, N., Mata, G., & O’Reilly, U.-M. (2021). Simulating a logistics enterprise using an asymmetrical wargame simulation
with soar reinforcement learning and coevolutionary algorithms. In K. Krawiec (Ed.), GECCO ’21: Genetic and Evolutionary Computation Conference, Companion
Volume, Lille, France, July 10-14, 2021 (pp. 1907–1915). ACM. https://doi.org/10.1145/3449726.3463172
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Srikant, S., Liu, S., Mitrovska, T., Chang, S., Fan, Q., Zhang, G., & O’Reilly, U.-M. (2021). Generating Adversarial Computer Programs using Optimized Obfuscations. 9th International Conference on Learning Representations, ICLR 2021,
Virtual Event, Austria, May 3-7, 2021. https://openreview.net/forum?id=PH5PH9ZO_4
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Shashkov, A., Gold, R., Hemberg, E., Kong, B. J., Bell, A., & O’Reilly, U.-M. (2021). Analyzing Student Reflection Sentiments and Problem-Solving Procedures
in MOOCs. In C. Meinel, Pérez-Sanagustı́n Mar, M. Specht, & A. Ogan (Eds.), L@S’21: Eighth ACM Conference on Learning @ Scale, Virtual Event,
Germany, June 22-25, 2021 (pp. 247–250). ACM. https://doi.org/10.1145/3430895.3460150
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O’Reilly, U.-M., & Devroey, X. (Eds.). (2021). Search-Based Software Engineering - 13th International Symposium,
SSBSE 2021, Bari, Italy, October 11-12, 2021, Proceedings (Vol. 12914). Springer. https://doi.org/10.1007/978-3-030-88106-1
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Toutouh, J., & O’Reilly, U.-M. (2021). Signal Propagation in a Gradient-Based and Evolutionary Learning System. CoRR, abs/2102.08929. https://arxiv.org/abs/2102.08929
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Srikant, S., Liu, S., Mitrovska, T., Chang, S., Fan, Q., Zhang, G., & O’Reilly, U.-M. (2021). Generating Adversarial Computer Programs using Optimized Obfuscations. CoRR, abs/2103.11882. https://arxiv.org/abs/2103.11882
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Karuna, P., Hemberg, E., O’Reilly, U.-M., & Rutar, N. (2021). Automating Cyber Threat Hunting Using NLP, Automated Query Generation,
and Genetic Perturbation. CoRR, abs/2104.11576. https://arxiv.org/abs/2104.11576
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Emanuello, J., Ferguson-Walter, K., Hemberg, E., O’Reilly, U.-M., Ridley, A., Ross, D., Staheli, D., & Streilein, W. W. (2021). Proceedings - AI/ML for Cybersecurity: Challenges, Solutions, and
Novel Ideas at SIAM Data Mining 2021. CoRR, abs/2104.13254. https://arxiv.org/abs/2104.13254
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Toutouh, J., Hemberg, E., & O’Reilly, U.-M. (2021). Fostering Diversity in Spatial Evolutionary Generative Adversarial
Networks. CoRR, abs/2106.13590. https://arxiv.org/abs/2106.13590
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Hemberg, E., & O’Reilly, U.-M. (2021). Using a Collated Cybersecurity Dataset for Machine Learning and Artificial
Intelligence. CoRR, abs/2108.02618. https://arxiv.org/abs/2108.02618
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Gunaratne, C., Reyes, R., Hemberg, E., & O’Reilly, U.-M. (2021). Evaluating Efficacy of Indoor Non-Pharmaceutical Interventions against
COVID-19 Outbreaks with a Coupled Spatial-SIR Agent-Based Simulation
Framework. CoRR, abs/2108.11025. https://arxiv.org/abs/2108.11025
2020
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O’Reilly, U.-M., Toutouh, J., Pertierra, M. A., Sanchez, D. P., Garcia, D., Lugo, A. E., Kelly, J., & Hemberg, E. (2020). Adversarial genetic programming for cyber security: a rising application
domain where GP matters. Genet. Program. Evolvable Mach., 21(1-2), 219–250. https://doi.org/10.1007/S10710-020-09389-Y
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Verwer, S., Nadeem, A., Hammerschmidt, C. A., Bliek, L., Al-Dujaili, A., & O’Reilly, U.-M. (2020). The Robust Malware Detection Challenge and Greedy Random Accelerated
Multi-Bit Search. In J. Ligatti & X. Ou (Eds.), AISec@CCS 2020: Proceedings of the 13th ACM Workshop on Artificial
Intelligence and Security, Virtual Event, USA, 13 November 2020 (pp. 61–70). ACM. https://doi.org/10.1145/3411508.3421374
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Toutouh, J., Hemberg, E., & O’Reilly, U.-M. (2020). Re-purposing heterogeneous generative ensembles with evolutionary
computation. In C. A. C. Coello (Ed.), GECCO ’20: Genetic and Evolutionary Computation Conference, Cancún
Mexico, July 8-12, 2020 (pp. 425–434). ACM. https://doi.org/10.1145/3377930.3390229
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O’Reilly, U.-M., & Hemberg, E. (2020). Genetic programming: a tutorial introduction. In C. A. C. Coello (Ed.), GECCO ’20: Genetic and Evolutionary Computation Conference, Companion
Volume, Cancún, Mexico, July 8-12, 2020 (pp. 512–525). ACM. https://doi.org/10.1145/3377929.3389882
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Shlapentokh-Rothman, M., Hemberg, E., & O’Reilly, U.-M. (2020). Securing the software defined perimeter with evolutionary co-optimization. In C. A. C. Coello (Ed.), GECCO ’20: Genetic and Evolutionary Computation Conference, Companion
Volume, Cancún, Mexico, July 8-12, 2020 (pp. 1528–1536). ACM. https://doi.org/10.1145/3377929.3398085
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Al-Dujaili, A., & O’Reilly, U.-M. (2020). Sign Bits Are All You Need for Black-Box Attacks. 8th International Conference on Learning Representations, ICLR 2020,
Addis Ababa, Ethiopia, April 26-30, 2020. https://openreview.net/forum?id=SygW0TEFwH
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Liu, S., Lu, S., Chen, X., Feng, Y., Xu, K., Al-Dujaili, A., Hong, M., & O’Reilly, U.-M. (2020). Min-Max Optimization without Gradients: Convergence and Applications
to Black-Box Evasion and Poisoning Attacks. Proceedings of the 37th International Conference on Machine Learning,
ICML 2020, 13-18 July 2020, Virtual Event, 119, 6282–6293. http://proceedings.mlr.press/v119/liu20j.html
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Pérez, E., Nesmachnow, S., Toutouh, J., Hemberg, E., & O’Reilly, U.-M. (2020). Parallel/distributed implementation of cellular training for generative
adversarial neural networks. 2020 IEEE International Parallel and Distributed Processing Symposium
Workshops, IPDPSW 2020, New Orleans, LA, USA, May 18-22, 2020, 512–518. https://doi.org/10.1109/IPDPSW50202.2020.00092
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Shen, H., Liang, L., Law, N., Hemberg, E., & O’Reilly, U.-M. (2020). Understanding Learner Behavior Through Learning Design Informed Learning
Analytics. In D. A. Joyner, R. F. Kizilcec, & S. Singer (Eds.), L@S’20: Seventh ACM Conference on Learning @ Scale, Virtual Event,
USA, August 12-14, 2020 (pp. 135–145). ACM. https://doi.org/10.1145/3386527.3405919
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Burd, H., Bell, A., Hemberg, E., & O’Reilly, U.-M. (2020). Analyzing Pre-Existing Knowledge and Performance in a Programming
MOOC. In D. A. Joyner, R. F. Kizilcec, & S. Singer (Eds.), L@S’20: Seventh ACM Conference on Learning @ Scale, Virtual Event,
USA, August 12-14, 2020 (pp. 281–284). ACM. https://doi.org/10.1145/3386527.3406728
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Gold, R., Hemberg, E., & O’Reilly, U.-M. (2020). Analyzing K-12 Blended MOOC Learning Behaviors. In D. A. Joyner, R. F. Kizilcec, & S. Singer (Eds.), L@S’20: Seventh ACM Conference on Learning @ Scale, Virtual Event,
USA, August 12-14, 2020 (pp. 345–348). ACM. https://doi.org/10.1145/3386527.3406743
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Toutouh, J., Hemberg, E., & O’Reilly, U.-M. (2020). Analyzing the Components of Distributed Coevolutionary GAN Training. In T. Bäck, M. Preuss, A. H. Deutz, H. Wang, C. Doerr, M. T. M. Emmerich, & H. Trautmann (Eds.), Parallel Problem Solving from Nature - PPSN XVI - 16th International
Conference, PPSN 2020, Leiden, The Netherlands, September 5-9, 2020,
Proceedings, Part I (Vol. 12269, pp. 552–566). Springer. https://doi.org/10.1007/978-3-030-58112-1_38
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Hemberg, E., Zhang, L., & O’Reilly, U.-M. (2020). Exploring Adversarial Artificial Intelligence for Autonomous Adaptive
Cyber Defense. In S. Jajodia, G. Cybenko, V. S. Subrahmanian, V. Swarup, C. Wang, & M. P. Wellman (Eds.), Adaptive Autonomous Secure Cyber Systems (pp. 41–61). Springer. https://doi.org/10.1007/978-3-030-33432-1_3
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Toutouh, J., Hemberg, E., & O’Reilly, U.-M. (2020). Data Dieting in GAN Training. In H. Iba & N. Noman (Eds.), Deep Neural Evolution - Deep Learning with Evolutionary Computation (pp. 379–400). Springer. https://doi.org/10.1007/978-981-15-3685-4_14
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Toutouh, J., Hemberg, E., & O’Reilly, U.-M. (2020). Re-purposing Heterogeneous Generative Ensembles with Evolutionary
Computation. CoRR, abs/2003.13532. https://arxiv.org/abs/2003.13532
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Toutouh, J., Hemberg, E., & O’Reilly, U.-M. (2020). Analyzing the Components of Distributed Coevolutionary GAN Training. CoRR, abs/2008.01124. https://arxiv.org/abs/2008.01124
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See Google Scholar and DBLP for older publications.