Xiaozhou Ye

Computer Vision and Pattern Recognition · with Wang · 2017–2018

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

Subfields

• Computer Vision and Pattern Recognition — 7 citations into it

Whom Xiaozhou Ye trusts overall

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

1. Yann LeCun
2. Yoshua Bengio

Papers from Xiaozhou Ye's perspective

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

1. Long Short-Term Memory
2. Rectified Linear Units Improve Restricted Boltzmann Machines
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Visualizing Data using t-SNE
7. Representation Learning: A Review and New Perspectives
8. Attention is All you Need (Neural Information Processing Systems)
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• HAST-IDS: Learning Hierarchical Spatial-Temporal Features Using Deep Neural Networks to Improve Intrusion Detection (2018) — 571 citations
• Malware traffic classification using convolutional neural network for representation learning (2017) — 924 citations