Mohamed M. Abdallah

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it
• Optimization & Training — 8 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it
• Federated & Distributed Learning — 5 citations into it

Whom Mohamed M. Abdallah trusts overall

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

1. Virginia Smith
2. Pierre Sermanet

Papers from Mohamed M. Abdallah's perspective

Ordered by how strongly the researchers Mohamed M. Abdallah trusts endorse each paper. Same corpus, a different order for every researcher.

1. Gradient-based learning applied to document recognition
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. TensorFlow: A system for large-scale machine learning
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. Learning Multiple Layers of Features from Tiny Images
7. Communication-Efficient Learning of Deep Networks from Decentralized Data
8. Federated Multi-Task Learning
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Optimal Distributed Online Prediction Using Mini-Batches

Their papers

• A Survey on Security and Privacy Issues in Edge-Computing-Assisted Internet of Things (2020) — 328 citations
• Exploiting Unlabeled Data in Smart Cities using Federated Learning (2020) — 20 citations