Insu Han

Artificial Intelligence · 2016–2018

A researcher in the Science corpus: 2 papers; trusts 18 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it; #22,922 of 35,345 by trust here, #31,361 by citations
• Statistics and Probability — 12 citations into it
• Optimization & Training — 9 citations into it
• Computational Mechanics — 8 citations into it; #7,636 of 10,001 by trust here, #9,582 by citations
• Computational Theory and Mathematics — 7 citations into it

Whom Insu Han trusts overall

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

1. Y. Saad
2. Michael F. Hutchinson
3. L. Eon Bottou
4. Martin A. Zinkevich
5. Tong Zhang
6. Andrew Gordon Wilson
7. Rie Johnson
8. Lin Xiao
9. Zeyuan Allen-Zhu
10. Dan Garber

Who trusts Insu Han overall

1. Jens Behrmann
2. David Kristjanson Duvenaud
3. Jörn-Henrik Jacobsen

Papers from Insu Han's perspective

Ordered by how strongly the researchers Insu Han 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Approximating the Spectral Sums of Large-scale Matrices using Chebyshev Approximations (2016) — 24 citations
• Stochastic Chebyshev Gradient Descent for Spectral Optimization (2018) — 11 citations