Justin Khim

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Management Science and Operations Research — 11 citations into it
• Statistics and Probability — 11 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Justin Khim trusts overall

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

1. Clayton D. Scott
2. John C. Duchi
3. Peter L. Bartlett
4. Srinadh Bhojanapalli
5. Zhi-Hua Zhou

Papers from Justin Khim's perspective

Ordered by how strongly the researchers Justin Khim 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. Categorical Reparameterization with Gumbel-Softmax
7. Spectrally-normalized margin bounds for neural networks
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Class-Weighted Classification: Trade-offs and Robust Approaches (2020) — 56 citations