| Using correlated information to extend device lifetime J Hribar, M Costa, N Kaminski, LA DaSilva IEEE Internet of Things Journal 6 (2), 2439-2448, 2018 | 52 | 2018 |
| A survey on securing federated learning: Analysis of applications, attacks, challenges, and trends HNC Neto, J Hribar, I Dusparic, DMF Mattos, NC Fernandes IEEE Access 11, 41928-41953, 2023 | 35 | 2023 |
| Utilising correlated information to improve the sustainability of internet of things devices J Hribar, L DaSilva 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), 805-808, 2019 | 21 | 2019 |
| Using deep Q-learning to prolong the lifetime of correlated internet of things devices J Hribar, A Marinescu, GA Ropokis, LA DaSilva 2019 IEEE International Conference on Communications Workshops (ICC …, 2019 | 19 | 2019 |
| Energy Aware Deep Reinforcement Learning Scheduling for Sensors Correlated in Time and Space J Hribar, A Marinescu, A Chiumento, LA Da Silva IEEE Internet of Things Journal, 2021 | 18 | 2021 |
| Updating strategies in the Internet of Things by taking advantage of correlated sources J Hribar, M Costa, N Kaminski, LA DaSilva GLOBECOM 2017-2017 IEEE Global Communications Conference, 1-6, 2017 | 17 | 2017 |
| Resource reservation within sliced 5G networks: A cost-reduction strategy for service providers JB Monteil, J Hribar, P Barnard, Y Li, LA DaSilva 2020 IEEE International Conference on Communications Workshops (ICC …, 2020 | 13 | 2020 |
| Federated spatial reuse optimization in next-generation decentralized ieee 802.11 WLANs F Wilhelmi, J Hribar, SF Yilmaz, E Ozfatura, K Ozfatura, O Yildiz, ... arXiv preprint arXiv:2203.10472, 2022 | 9 | 2022 |
| Smart: Situationally-aware multi-agent reinforcement learning-based transmissions Z Jiang, Y Liu, J Hribar, LA DaSilva, S Zhou, Z Niu IEEE Transactions on Cognitive Communications and Networking 7 (4), 1430-1443, 2021 | 7 | 2021 |
| Timely and sustainable: Utilising correlation in status updates of battery-powered and energy-harvesting sensors using Deep Reinforcement Learning J Hribar, LA DaSilva, S Zhou, Z Jiang, I Dusparic Computer Communications 192, 223-233, 2022 | 6 | 2022 |
| Fedsbs: Federated-learning participant-selection method for intrusion detection systems HNC Neto, J Hribar, I Dusparic, NC Fernandes, DMF Mattos Computer Networks 244, 110351, 2024 | 5 | 2024 |
| Digital transformation with a lightweight on-premise PaaS D Mušić, J Hribar, C Fortuna Future Generation Computer Systems 160, 619-629, 2024 | 4 | 2024 |
| Visibility graph based wireless anomaly detection for digital twin edge networks B Bertalanič, J Hribar, C Fortuna IEEE Open Journal of the Communications Society, 2024 | 3 | 2024 |
| Deep w-networks: Solving multi-objective optimisation problems with deep reinforcement learning J Hribar, L Hackett, I Dusparic arXiv preprint arXiv:2211.04813, 2022 | 3 | 2022 |
| Analyse or Transmit: Utilising Correlation at the Edge with Deep Reinforcement Learning J Hribar, R Shinkuma, G Iosifidis, I Dusparic 2021 IEEE Global Communications Conference (GLOBECOM), 2021 | 3 | 2021 |
| The energy cost of artificial intelligence of things lifecycle SK Chou, J Hribar, M Mohorčič, C Fortuna arXiv preprint arXiv:2408.00540, 2024 | 2 | 2024 |
| Machine Learning Operations Model Store: Optimizing Model Selection for AI as a Service G Cerar, J Hribar 2023 International Balkan Conference on Communications and Networking …, 2023 | 2 | 2023 |
| Smart home energy cost minimisation using energy trading with deep reinforcement learning M Pokorn, M Mohorčič, A Čampa, J Hribar Proceedings of the 10th ACM International Conference on Systems for Energy …, 2023 | 1 | 2023 |
| Method and system for energy aware scheduling for sensors L Da Silva, J Hribar US Patent 11,762,446, 2023 | 1 | 2023 |
| Enabling Deep Reinforcement Learning on Energy Constrained Devices at the Edge of the Network J Hribar, I Dusparic 2022 IEEE Wireless Communications and Networking Conference (WCNC), 2022 | 1 | 2022 |
Luiz DaSilvaVirginia Techایمیل تأیید شده در vt.edu