U. Kang

Artificial Intelligence · with Kim · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 38 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Computer Vision and Pattern Recognition — 21 citations into it
• Information Systems — 16 citations into it
• Model Architectures — 5 citations into it
• Optimization & Training — 5 citations into it
• Recommender Systems — 5 citations into it

Whom U. Kang trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Alex Krizhevsky
4. Yoshua Bengio
5. Kaiming He
6. Ruslan Salakhutdinov
7. Sergey Ioffe
8. Diederik P. Kingma
9. Ilya Sutskever
10. Christian Szegedy

Papers from U. Kang's perspective

Ordered by how strongly the researchers U. Kang 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. Learning Multiple Layers of Features from Tiny Images
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet: A large-scale hierarchical image database
10. Distilling the Knowledge in a Neural Network (arXiv.org)

Their papers

• Knowledge Extraction with No Observable Data (2019) — 109 citations
• UniWalk: Explainable and Accurate Recommendation for Rating and Network Data (2017) — 37 citations