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All Outputs (71)

On the Termination of Flooding (2020)
Presentation / Conference Contribution
Hussak, W., & Trehan, A. (2020, December). On the Termination of Flooding. Presented at 37th International Symposium on Theoretical Aspects of Computer Science (STACS 2020), Dagstuhl, Germany

Fully Compact Routing in Low Memory Self-Healing Trees (2020)
Presentation / Conference Contribution
Castañeda, A., Lefévre, J., & Trehan, A. (2020, December). Fully Compact Routing in Low Memory Self-Healing Trees. Presented at Proceedings of the 21st International Conference on Distributed Computing and Networking, New York, NY, USA

The relationship between trust in AI and trustworthy machine learning technologies (2020)
Presentation / Conference Contribution
Toreini, E., Aitken, M., Coopamootoo, K., Elliott, K., Zelaya, C. G., & van Moorsel, A. (2020, December). The relationship between trust in AI and trustworthy machine learning technologies. Presented at Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency

Towards an assessment grid for intelligent modeling assistance (2020)
Presentation / Conference Contribution
Mussbacher, G., Combemale, B., Abrahão, S., Bencomo, N., Burgueño, L., Engels, G., Kienzle, J., Kühn, T., Mosser, S., Sahraoui, H. A., Weyssow, M., Guerra, E., & Iovino, L. (2020, December). Towards an assessment grid for intelligent modeling assistance. Presented at MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems, Virtual Event, Canada, 18-23 October, 2020, Companion Proceedings

SYNTHETIC CROWD AND PEDESTRIAN GENERATOR FOR DEEP LEARNING PROBLEMS (2020)
Presentation / Conference Contribution
Khadka, A., Remagnino, P., & Argyriou, V. (2020, December). SYNTHETIC CROWD AND PEDESTRIAN GENERATOR FOR DEEP LEARNING PROBLEMS. Presented at 2020 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING Inst Elect \& Elect Engineers; Inst Elect \& Elect Engineers, Signal Proc Soc

Modelling Hierarchical Key Structure With Pitch Scapes (2020)
Presentation / Conference Contribution
Lieck, R., & Rohrmeier, M. (2020, December). Modelling Hierarchical Key Structure With Pitch Scapes. Presented at Proceedings of the 21st International Society for Music Information Retrieval Conference, Montréal, Canada

Automated provenance graphs for models@run.time (2020)
Presentation / Conference Contribution
Reynolds, O., García-Domínguez, A., & Bencomo, N. (2020, December). Automated provenance graphs for models@run.time. Presented at MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems, Virtual Event, Canada, 18-23 October, 2020, Companion Proceedings

Run-time and Collective Adaptation of Gameful Systems (2020)
Presentation / Conference Contribution
Bucchiarone, A., Bencomo, N., Loria, E., Marconi, A., & Cicchetti, A. (2020, December). Run-time and Collective Adaptation of Gameful Systems. Presented at 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems, ACSOS 2020, Companion Volume, Washington, DC, USA, August 17-21, 2020

Automatic Subject-based Contextualisation of Programming Assignment Lists (2020)
Presentation / Conference Contribution
Fonseca, S. C., Pereira, F. D., Oliveira, E. H., Oliveira, D. B., Carvalho, L. S., & Cristea, A. I. (2020, December). Automatic Subject-based Contextualisation of Programming Assignment Lists. Presented at Educational Data Mining 2020 (EDM), Virtual

As programming must be learned by doing, introductory programming course learners need to solve many problems, e.g., on systems such as ’Online Judges’. However, as such courses are often compulsory for non-Computer Science (nonCS) undergraduates, th... Read More about Automatic Subject-based Contextualisation of Programming Assignment Lists.

Accurate Deep Net Crowd Counting for Smart IoT Video acquisition devices (2020)
Presentation / Conference Contribution
Khadka, A., Argyriou, V., & Remagnino, P. (2020, December). Accurate Deep Net Crowd Counting for Smart IoT Video acquisition devices. Presented at 16TH ANNUAL INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING IN SENSOR SYSTEMS (DCOSS 2020) IEEE Comp Soc

Singularly Optimal Randomized Leader Election (2020)
Presentation / Conference Contribution
Kutten, S., Moses Jr., W. K., Pandurangan, G., & Peleg, D. (2020, December). Singularly Optimal Randomized Leader Election. Presented at 34th International Symposium on Distributed Computing (DISC 2020)

Temporal Models for History-Aware Explainability (2020)
Presentation / Conference Contribution
Ullauri, J. M. P., García-Domínguez, A., Paucar, L. H. G., & Bencomo, N. (2020, October). Temporal Models for History-Aware Explainability. Presented at SAM '20: 12th System Analysis and Modelling Conference, (Online) Canada

On one hand, there has been a growing interest towards the application of AI-based learning and evolutionary programming for self-adaptation under uncertainty. On the other hand, self-explanation is one of the self-* properties that has been neglecte... Read More about Temporal Models for History-Aware Explainability.