Daiki Tanaka

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it; #19,815 of 35,345 by trust here, #13,962 by citations
• Computer Vision and Pattern Recognition — 10 citations into it; #12,386 of 21,575 by trust here, #9,563 by citations
• Optimization & Training — 6 citations into it

Whom Daiki Tanaka trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Arash Vahdat
4. X. Zhang
5. Geoffrey E. Hinton
6. Shaoqing Ren
7. Yoshua Bengio
8. David Arthur
9. Christian Szegedy
10. Diederik P. Kingma

Who trusts Daiki Tanaka overall

1. Junnan Li
2. Pengfei Chen
3. Görkem Algan
4. Dongkai Wang
5. Haiyang Zhang
6. Peixiang Zhong
7. Hongxin Wei
8. Hrayr Harutyunyan
9. Elad Amrani
10. Youngdong Kim

Papers from Daiki Tanaka's perspective

Ordered by how strongly the researchers Daiki Tanaka 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Joint Optimization Framework for Learning with Noisy Labels (2018) — 806 citations