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Naji Alhusaini
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2020 – today
- 2024
- [c4]Cheng Wu, Hong Zhong, Guilin Chen, Naji Alhusaini, Shenghui Zhao, Yuchen Zhang:
Optimizing Multimodal Federated Learning: Novel Approaches for Efficient Model Aggregation and Client Sampling. NaNA 2024: 137-146 - [c3]Yuchen Zhang, Hong Zhong, Guilin Chen, Naji Alhusaini, Shenghui Zhao, Cheng Wu:
Multimodal Sentiment Analysis Network Based on Distributional Transformation and Gated Cross-Modal Fusion. NaNA 2024: 496-503 - 2022
- [c2]Naji Alhusaini, Jing Li, Philippe Fournier-Viger, Ammar Hawbani, Guilin Chen:
Mining High Utility Itemset with Multiple Minimum Utility Thresholds Based on Utility Deviation. ICDM (Workshops) 2022: 490-496 - [c1]M. Saqib Nawaz, Philippe Fournier-Viger, Naji Alhusaini, Yulin He, Youxi Wu, Debdatta Bhattacharya:
LCIM: Mining Low Cost High Utility Itemsets. MIWAI 2022: 73-85 - [i1]Yifan Wang, Wei Fan, Keke Yang, Naji Alhusaini, Jing Li:
A Knowledge Distillation-Based Backdoor Attack in Federated Learning. CoRR abs/2208.06176 (2022) - 2021
- [j5]Aiman Ghannami, Jing Li, Ammar Hawbani, Naji Alhusaini:
Diversity metrics for direct-coded variable-length chromosome shortest path problem evolutionary algorithms. Computing 103(2): 313-332 (2021) - [j4]Khadija Kanwal, Khawaja Tehseen Ahmad, Rashid Khan, Naji Alhusaini, Jing Li:
Deep Learning Using Isotroping, Laplacing, Eigenvalues Interpolative Binding, and Convolved Determinants with Normed Mapping for Large-Scale Image Retrieval. Sensors 21(4): 1139 (2021) - 2020
- [j3]Mahwish Yousaf, Tanzeel U. Rehman, Dongliang Liao, Naji Alhusaini, Jing Li:
FastIsomapVis: A Novel Approach for Nonlinear Manifold Learning. IEEE Access 8: 199470-199481 (2020) - [j2]Mohammed Abbas Mohammed Almansor, Chongfu Zhang, Wasiq Khan, Abir Hussain, Naji Alhusaini:
Cross Lingual Sentiment Analysis: A Clustering-Based Bee Colony Instance Selection and Target-Based Feature Weighting Approach. Sensors 20(18): 5276 (2020)
2010 – 2019
- 2019
- [j1]Naji Alhusaini, Saleem Karmoshi, Ammar Hawbani, Jing Li, Abdullah Alhusaini, Yaser Al-Sharabi:
LUIM: New Low-Utility Itemset Mining Framework. IEEE Access 7: 100535-100551 (2019)
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