Steven R. Young

Artificial Intelligence · 2015–2017

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Optimization & Training — 9 citations into it

Whom Steven R. Young trusts overall

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

1. James Bergstra
2. Alex Krizhevsky
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Hugo Larochelle
6. Jasper Snoek
7. Kaiming He
8. Yann LeCun
9. Yangqing Jia
10. Diederik P. Kingma

Who trusts Steven R. Young overall

1. Andrea Soltoggio
2. Tal Ben-Nun
3. Chaoyue Wang
4. Quanming Yao
5. Max Jaderberg
6. Kenneth O. Stanley
7. Torsten Hoefler
8. Chang Xu

Papers from Steven R. Young's perspective

Ordered by how strongly the researchers Steven R. Young 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Optimizing deep learning hyper-parameters through an evolutionary algorithm (2015) — 435 citations
• Evolving Deep Networks Using HPC (2017) — 45 citations