Zeye (Dexter) Liu

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 9 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 — 18 citations into it
• Efficiency & Compression — 16 citations into it
• Model Architectures — 5 citations into it

Whom Zeye (Dexter) Liu trusts overall

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

1. Matthieu Courbariaux
2. Diederik P. Kingma
3. Yoshua Bengio
4. Andrew L. Maas
5. Kaiming He
6. Suyog Gupta
7. Geoffrey E. Hinton
8. Dimitrios Stamoulis
9. Jimmy Ba
10. Alex Krizhevsky

Who trusts Zeye (Dexter) Liu overall

1. Dimitrios Stamoulis

Papers from Zeye (Dexter) Liu's perspective

Ordered by how strongly the researchers Zeye (Dexter) Liu 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet: A large-scale hierarchical image database

Their papers

• LightNN: Filling the Gap between Conventional Deep Neural Networks and Binarized Networks (2017) — 38 citations
• FLightNNs: Lightweight Quantized Deep Neural Networks for Fast and Accurate Inference (2019) — 26 citations