Urban water flow and water level prediction based on deep learning H Assem, S Ghariba, G Makrai, P Johnston, L Gill, F Pilla Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 81 | 2017 |
Monitoring VoIP call quality using improved simplified E-model H Assem, D Malone, J Dunne, P O'Sullivan 2013 International Conference on Computing, Networking and Communications …, 2013 | 81 | 2013 |
Deepad: A generic framework based on deep learning for time series anomaly detection TS Buda, B Caglayan, H Assem Pacific-Asia conference on knowledge discovery and data mining, 577-588, 2018 | 72 | 2018 |
Big data analytics for sensor-network collected intelligence HH Hsu, CY Chang, CH Hsu Morgan Kaufmann, 2017 | 50 | 2017 |
Can machine learning aid in delivering new use cases and scenarios in 5G? TS Buda, H Assem, L Xu, D Raz, U Margolin, E Rosensweig, DR Lopez, ... NOMS 2016-2016 IEEE/IFIP Network Operations and Management Symposium, 1279-1284, 2016 | 47 | 2016 |
CogNet: A network management architecture featuring cognitive capabilities L Xu, H Assem, IGB Yahia, TS Buda, A Martin, D Gallico, M Biancani, ... 2016 European Conference on Networks and Communications (EuCNC), 325-329, 2016 | 39 | 2016 |
Rule-based adaptive monitoring of application performance ER Altman, HAAA Salama, NM Mitchell, PJ O'Sullivan, AOP DOMINGUEZ, ... US Patent 10,078,571, 2018 | 38 | 2018 |
Spatio-temporal clustering approach for detecting functional regions in cities H Assem, L Xu, TS Buda, D O'Sullivan 2016 IEEE 28th international conference on tools with artificial …, 2016 | 33 | 2016 |
View on 5G architecture S Redana, A Kaloxylos, A Galis, P Rost, V Jungnickel White paper of the 5G-PPP architecture WG, 2016 | 33 | 2016 |
Machine learning as a service for enabling Internet of Things and People H Assem, L Xu, TS Buda, D O’Sullivan Personal and Ubiquitous Computing 20, 899-914, 2016 | 32 | 2016 |
RCMC: Recognizing crowd-mobility patterns in cities based on location based social networks data H Assem, TS Buda, D O’sullivan ACM Transactions on Intelligent Systems and Technology (TIST) 8 (5), 1-30, 2017 | 20 | 2017 |
Dynamically adapting a test workload to accelerate the identification of performance issues ER Altman, HAAA Salama, NM Mitchell, PJ O'Sullivan, AOP DOMINGUEZ, ... US Patent 10,176,022, 2019 | 19 | 2019 |
Monitoring voice over internet protocol (VoIP) quality during an ongoing call H Assem, J Dunne, JP Galvin Jr, PJ O'sullivan US Patent 9,325,838, 2016 | 19 | 2016 |
Analysis of machine learning techniques for anomaly detection in the internet of things S Brady, D Magoni, J Murphy, H Assem, AO Portillo-Dominguez 2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI), 1-6, 2018 | 18 | 2018 |
Collaboration group recommendations derived from request-action correlations HAAA Salama, A Chakra, JD Dunne, LS Harpur US Patent 9,916,605, 2018 | 17 | 2018 |
Cross-lingual sentence embedding using multi-task learning K Goswami, S Dutta, H Assem, T Fransen, JP McCrae Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 16 | 2021 |
St-dennetfus: A new deep learning approach for network demand prediction H Assem, B Caglayan, TS Buda, D O’Sullivan Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018 | 16 | 2018 |
ADE: An ensemble approach for early Anomaly Detection TS Buda, H Assem, L Xu 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM …, 2017 | 16 | 2017 |
Anomaly detection B Teodora, HAAA Salama, B Caglayan, F Ghaffar US Patent 11,860,971, 2024 | 13 | 2024 |
Quality of experience for communication sessions J Dunne, JP Galvin Jr, PJ O'sullivan, HAAA Salama US Patent 9,397,947, 2016 | 13 | 2016 |