Ms Tahani Aladwani
- Research Assistant (Computing Science)
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Aladwani, T. and Anagnostopoulos, C. (2024) Semi-Supervised Federated Learning over Relevant Heterogeneous Data. In: BMVC 2024 Workshop on Privacy, Fairness, Accountability and Transparency in Computer Vision, Glasgow, UK, 28 November 2024, (Accepted for Publication)
Aladwani, T., Anagnostopoulos, C. and Kolomvatsos, K. (2024) Node and relevant data selection in distributed predictive analytics: a query-centric approach. Journal of Network and Computer Applications, (Accepted for Publication)
Aladwani, T., Anagnostopoulos, C. , Puthiya Parambath, S. and Deligianni, F. (2024) CL-FML: Cluster-based & Label-aware Federated Meta-Learning for On-Demand Classification Tasks. In: 11th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2024), San Diego, CA, United States, 6-10 October 2024, (Accepted for Publication)
Aladwani, T., Parambath, S. , Anagnostopoulos, C. and Deligianni, F. (2024) The Price of Labelling: A Two-Phase Federated Self-Learning Approach. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), Vilnius, Lithuania, 9-13 September 2024, (Accepted for Publication)
Aladwani, T., Anagnostopoulos, C. , Kolomvatsos, K., Alghamdi, I. and Deligianni, F. (2023) Query-driven Edge Node Selection in Distributed Learning Environments. In: Data-driven Smart Cities (DASC 2023)/ 39th IEEE International Conference on Data Engineering (ICDE 2023), Anaheim, CA, United States, 3-7 April 2023, pp. 146-153. ISBN 9798350322446 (doi: 10.1109/ICDEW58674.2023.00029)
Anagnostopoulos, C. , Aladwani, T., Alghamdi, I. and Kolomvatsos, K. (2022) Data-driven analytics task management reasoning mechanism in edge computing. Smart Cities, 5(2), pp. 562-582. (doi: 10.3390/smartcities5020030)
Aladwani, T., Alghamdi, I., Kolomvatsos, K. and Anagnostopoulos, C. (2022) Data-Driven Analytics Task Management at the Edge: A Fuzzy Reasoning Approach. In: 9th International Conference on Future Internet of Things and Cloud (FiCloud 2022), Rome, Italy, 22-24 August 2022, pp. 83-91. ISBN 9781665493505 (doi: 10.1109/FiCloud57274.2022.00019)
Aladwani, T., Anagnostopoulos, C. and Kolomvatsos, K. (2024) Node and relevant data selection in distributed predictive analytics: a query-centric approach. Journal of Network and Computer Applications, (Accepted for Publication)
Anagnostopoulos, C. , Aladwani, T., Alghamdi, I. and Kolomvatsos, K. (2022) Data-driven analytics task management reasoning mechanism in edge computing. Smart Cities, 5(2), pp. 562-582. (doi: 10.3390/smartcities5020030)
Aladwani, T. and Anagnostopoulos, C. (2024) Semi-Supervised Federated Learning over Relevant Heterogeneous Data. In: BMVC 2024 Workshop on Privacy, Fairness, Accountability and Transparency in Computer Vision, Glasgow, UK, 28 November 2024, (Accepted for Publication)
Aladwani, T., Anagnostopoulos, C. , Puthiya Parambath, S. and Deligianni, F. (2024) CL-FML: Cluster-based & Label-aware Federated Meta-Learning for On-Demand Classification Tasks. In: 11th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2024), San Diego, CA, United States, 6-10 October 2024, (Accepted for Publication)
Aladwani, T., Parambath, S. , Anagnostopoulos, C. and Deligianni, F. (2024) The Price of Labelling: A Two-Phase Federated Self-Learning Approach. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), Vilnius, Lithuania, 9-13 September 2024, (Accepted for Publication)
Aladwani, T., Anagnostopoulos, C. , Kolomvatsos, K., Alghamdi, I. and Deligianni, F. (2023) Query-driven Edge Node Selection in Distributed Learning Environments. In: Data-driven Smart Cities (DASC 2023)/ 39th IEEE International Conference on Data Engineering (ICDE 2023), Anaheim, CA, United States, 3-7 April 2023, pp. 146-153. ISBN 9798350322446 (doi: 10.1109/ICDEW58674.2023.00029)
Aladwani, T., Alghamdi, I., Kolomvatsos, K. and Anagnostopoulos, C. (2022) Data-Driven Analytics Task Management at the Edge: A Fuzzy Reasoning Approach. In: 9th International Conference on Future Internet of Things and Cloud (FiCloud 2022), Rome, Italy, 22-24 August 2022, pp. 83-91. ISBN 9781665493505 (doi: 10.1109/FiCloud57274.2022.00019)