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Found 168 results
Author Title [ Type(Desc)] Year
Filters: Author is Felix Freitag
Conference Paper
R. Tous., Freitag, F., and Berral., J., On the Relation Between Open Project-Based Learning in Undergraduate Computer Science Education and Contemporary Technological Trends, in Proceedings of the 16th International Conference on Computer Supported Education - Volume 2: CSEDU, 2024.
Journal Article
N. Llisterri Giménez, Solé, J. Miquel, and Freitag, F., Embedded federated learning over a LoRa mesh network, Pervasive and Mobile Computing, vol. 93, p. 101819, 2023.
Conference Paper
E. Cruz Harillo and Freitag, F., Exploring Blockchain-Based Management For LoRa IoT Nodes, in Economics of Grids, Clouds, Systems, and Services: 19th International Conference, GECON 2022, Izola, Slovenia, September 13–15, 2022, Proceedings, Berlin, Heidelberg, 2023.
S. Aatab and Freitag, F., Integrating a Neural Network Library in Embedded Federated Learning, in 2023 IEEE 6th International Conference on Cloud Computing and Artificial Intelligence: Technologies and Applications (CloudTech), 2023.
Conference Paper
F. Freitag, Solé, J. Miquel, and Meseguer, R., Position Paper: LoRa Mesh Networks for Enabling Distributed Intelligence on Tiny IoT Nodes, in Workshop Proceedings of the 19th International Conference on Intelligent Environments (IE2023), Mauritius, 27-30 June 2023, 2023.
F. Freitag, Wei, L., Liu, C. - H., Selimi, M., and Veiga, L., Server-side Adaptive Federated Learning over Wireless Mesh Network, in Information Technology and Systems (ICITS 2023), Cusco, Peru, 2023.
J. Francisco, Coimbra, M. E., Neto, P. Fernandes, Freitag, F., and Veiga, L., Stateful Adaptive Streams with Approximate Computing and Elastic Scaling, in Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, New York, NY, USA, 2023.
S. Aatab and Freitag, F., Towards a Library of Deep Neural Networks for Experimenting with on-Device Training on Microcontrollers, in 2023 IEEE 9th World Forum on Internet of Things (WF-IoT), 2023.
N. Llisterri Gimenez, Freitag, F., Lee, J. K., and Vandierendonck, H., Comparison of Two Microcontroller Boards for On-Device Model Training in a Keyword Spotting Task, in 2022 11th Mediterranean Conference on Embedded Computing (MECO), 2022, pp. 1-4.
Conference Proceedings
F. Freitag, Vilchez, P., Wei, L., Liu, C. - H., Selimi, M., and Koutsopoulos, I., Demo: An Experimental Environment Based On Mini-PCs For Federated Learning Research, 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC). IEEE, Las Vegas, 2022.
Conference Paper
J. Miquel Solé, Nogués, S. Miralles, Pueyo-Centelles, R., and Freitag, F., Demonstration of a library prototype to build LoRa mesh networks for the IoT, in 2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS), 2022.
D. Lopez Pino, Freitag, F., and Selimi, M., Designing a Double LoRa Connectivity for the Arduino Portenta H7, in 2022 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN), 2022.
Journal Article
J. Miquel Solé, Pueyo-Centelles, R., Freitag, F., and Meseguer, R., Implementation of a LoRa Mesh Library, IEEE Access, vol. 10, pp. 113158-113171, 2022.
Conference Paper
E. Cruz Harillo and Freitag, F., LoRaCoin: Towards a blockchain-based platform for managing LoRa devices, in IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2022, pp. 1-2.
Book Chapter
F. Freitag, Vilchez, P., Wei, L., Liu, C. - H., and Selimi, M., Performance Evaluation of Federated Learning Over Wireless Mesh Networks with Low-Capacity Devices, in The 2022 International Conference on Information Technology & Systems, online: Springer International Publishing, 2022, p. 635--645.
Conference Paper
A. Jesus Cape Del Solar, Solé, J. Miquel, and Freitag, F., Towards a Monitoring System for a LoRa Mesh Network, in 2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS), 2022.
L. Ibraimi, Selimi, M., and Freitag, F., BePOCH: Improving Federated Learning Performance in Resource-Constrained Computing Devices, in 2021 IEEE Global Communications Conference (GLOBECOM), Madrid, 2021.
Conference Paper
M. Monfort Grau, Pueyo-Centelles, R., and Freitag, F., On-Device Training of Machine Learning Models on Microcontrollers With a Look at Federated Learning, in Proceedings of the Conference on Information Technology for Social Good, New York, NY, USA, 2021, pp. 198–203.

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