Yi-gui Ou

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it
• Optimization & Training — 8 citations into it

Whom Yi-gui Ou trusts overall

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

1. James Martens
2. Boris Polyak
3. Diederik P. Kingma

Papers from Yi-gui Ou's perspective

Ordered by how strongly the researchers Yi-gui Ou trusts endorse each paper. Same corpus, a different order for every researcher.

1. Long Short-Term Memory
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
4. On the importance of initialization and momentum in deep learning
5. Deep learning via Hessian-free optimization
6. Deep Learning
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. ImageNet classification with deep convolutional neural networks
9. Optimizing Neural Networks with Kronecker-factored Approximate Curvature
10. Gradient-based learning applied to document recognition

Their papers

• Revisiting Recursive Least Squares for Training Deep Neural Networks (2021) — 7 citations