Ying Shi

Artificial Intelligence · with Tang · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Signal Processing — 14 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Model Architectures — 5 citations into it

Whom Ying Shi trusts overall

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

1. Daniel Povey
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Sergey Ioffe
5. Alex Graves
6. Karen Simonyan
7. Kyunghyun Cho
8. Kaiming He
9. Alex Krizhevsky
10. Yann LeCun

Papers from Ying Shi's perspective

Ordered by how strongly the researchers Ying Shi 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Deep Speaker Feature Learning for Text-Independent Speaker Verification (2017) — 89 citations
• Memory visualization for gated recurrent neural networks in speech recognition (2016) — 56 citations