Fadi A. Thabtah

Information Systems · 2007–2020

A researcher in the Science corpus: 5 papers; trusts 40 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 28 citations into it; #2,935 of 8,771 by trust here, #4,518 by citations
• Artificial Intelligence — 23 citations into it; #15,235 of 35,345 by trust here, #20,377 by citations
• Signal Processing — 13 citations into it
• Algorithms & Complexity — 8 citations into it
• Computational Theory and Mathematics — 7 citations into it; #4,766 of 12,182 by trust here, #7,501 by citations
• Statistical Learning Theory — 7 citations into it
• Optimization & Training — 7 citations into it
• Sociology and Political Science — 5 citations into it

Whom Fadi A. Thabtah trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. J. Ross Quinlan
2. B. Liu
3. Jiawei Han
4. Mohammed J. Zaki
5. William W. Cohen
6. Robert E. Schapire
7. Peter Clark
8. Xiaoxin Yin
9. Amanda Clare
10. Wynne Hsu

Who trusts Fadi A. Thabtah overall

1. Cynthia Rudin
2. Benjamin Letham
3. Allison Chang
4. David Madigan
5. Yanfang Ye
6. Fernando Martínez-Plumed

Papers from Fadi A. Thabtah's perspective

Ordered by how strongly the researchers Fadi A. Thabtah trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Attention is All you Need (Neural Information Processing Systems)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• A review of associative classification mining (2007) — 324 citations
• A machine learning framework for sport result prediction (2019) — 302 citations
• Data imbalance in classification: Experimental evaluation (2020) — 773 citations
• Phishing detection based Associative Classification data mining (2014) — 405 citations
• Predicting phishing websites based on self-structuring neural network (2013) — 351 citations