Yuang Jiang

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 45 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Efficiency & Compression — 24 citations into it
• Federated & Distributed Learning — 13 citations into it

Whom Yuang Jiang trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Yoshua Bengio
6. Kaiming He
7. Andrew Zisserman
8. H. Brendan McMahan
9. Diederik P. Kingma
10. L. Eon Bottou

Who trusts Yuang Jiang overall

1. Samuel Horváth

Papers from Yuang Jiang's perspective

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

Their papers

• Model Pruning Enables Efficient Federated Learning on Edge Devices (2019) — 650 citations