Abdullatif Albaseer

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it
• Optimization & Training — 8 citations into it
• Federated & Distributed Learning — 5 citations into it

Whom Abdullatif Albaseer trusts overall

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

1. Virginia Smith
2. Pierre Sermanet
3. Yann LeCun
4. Tao Lin
5. H. Brendan McMahan
6. Ofer Dekel
7. Anit Kumar Sahu
8. Ohad Shamir
9. Sebastian U. Stich
10. Maziar Sanjabi

Papers from Abdullatif Albaseer's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Gradient-based learning applied to document recognition
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Exploiting Unlabeled Data in Smart Cities using Federated Learning (2020) — 20 citations