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2020 – today
- 2023
[j3]Thaha Mohammed
, Si-Ahmed Naas, Stephan Sigg, Mario Di Francesco:
Knowledge Sharing in AI Services: A Market-Based Approach. IEEE Internet Things J. 10(2): 1320-1331 (2023)- [c6]Si-Ahmed Naas, Stephan Sigg:
Fast converging Federated Learning with Non-IID Data. VTC2023-Spring 2023: 1-6 - 2022
- [j2]Jing Ma, Si-Ahmed Naas, Stephan Sigg, Xixiang Lyu:
Privacy-preserving federated learning based on multi-key homomorphic encryption. Int. J. Intell. Syst. 37(9): 5880-5901 (2022) - 2021
- [c5]Andreas Hitz, Si-Ahmed Naas, Stephan Sigg:
Sharing geotagged pictures for an Emotion-based Recommender System. PerCom Workshops 2021: 68-73 - [i1]Jing Ma, Si-Ahmed Naas, Stephan Sigg, Xixiang Lyu:
Privacy-preserving Federated Learning based on Multi-key Homomorphic Encryption. CoRR abs/2104.06824 (2021) - 2020
- [j1]Xiaolan Jiang, Si-Ahmed Naas, Yi-Han Chiang, Stephan Sigg, Yusheng Ji:
SVP: Sinusoidal Viewport Prediction for 360-Degree Video Streaming. IEEE Access 8: 164471-164481 (2020) - [c4]Si-Ahmed Naas, Xiaolan Jiang, Stephan Sigg, Yusheng Ji:
Functional gaze prediction in egocentric video. MoMM 2020: 40-47 - [c3]Si-Ahmed Naas, Thaha Mohammed, Stephan Sigg:
A Global Brain fuelled by Local intelligence: Optimizing Mobile Services and Networks with AI. MSN 2020: 23-32 - [c2]Si-Ahmed Naas, Stephan Sigg:
Real-time Emotion Recognition for Sales. MSN 2020: 584-591
2010 – 2019
- 2018
- [c1]Tarik Taleb, Miloud Bagaa, Si-Ahmed Naas:
Scheduled Communications in Next Generationmobile Networks. GLOBECOM 2018: 1-6
Coauthor Index
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