Tommy M. Tang

Optimization & Training · 2020

A researcher in the Science corpus: 1 paper; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 35 citations into it
• Artificial Intelligence — 21 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Generative Models — 8 citations into it

Whom Tommy M. Tang trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Alex Graves
6. Ilya Sutskever
7. Kaiming He
8. James Martens
9. Ian J. Goodfellow
10. Matthew D. Zeiler

Who trusts Tommy M. Tang overall

1. Mohamed Reyad

Papers from Tommy M. Tang's perspective

Ordered by how strongly the researchers Tommy M. Tang 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients (2020) — 669 citations