Yaming Yang

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it
• Computer Vision and Pattern Recognition — 38 citations into it
• Efficiency & Compression — 26 citations into it
• Optimization & Training — 10 citations into it
• Model Architectures — 7 citations into it

Whom Yaming Yang trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Barret Zoph

Papers from Yaming Yang's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Distilling the Knowledge in a Neural Network (arXiv.org)
4. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression (2020) — 81 citations
• Deeper Insights into Weight Sharing in Neural Architecture Search (2020) — 55 citations