Yuanyuan Liu

Optimization & Training · with Cheng · 2018

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 33 citations into it
• Artificial Intelligence — 29 citations into it
• Computational Mechanics — 21 citations into it
• Management Science and Operations Research — 6 citations into it
• Mathematical Optimization — 5 citations into it

Whom Yuanyuan Liu trusts overall

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

1. Yurii E. Nesterov
2. Tong Zhang
3. Zeyuan Allen-Zhu
4. Shai Shalev-Shwartz
5. Julien Mairal
6. Alex Krizhevsky
7. Francis R. Bach
8. Guanghui Lan
9. Geoffrey E. Hinton
10. Mark W. Schmidt

Papers from Yuanyuan Liu's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization (2018) — 9 citations