Yusuke Koda

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it
• Federated & Distributed Learning — 10 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Efficiency & Compression — 8 citations into it

Whom Yusuke Koda trusts overall

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

1. Otkrist Gupta
2. Geoffrey E. Hinton
3. Ilya Sutskever
4. Yann LeCun
5. Yoshua Bengio
6. Praneeth Vepakomma
7. Alex Krizhevsky
8. Ramesh Raskar
9. James Martens
10. Diederik P. Kingma

Who trusts Yusuke Koda overall

1. Praneeth Vepakomma
2. Jihong Park
3. Abhishek Singh
4. Minrui Xu
5. Chaoyang He

Papers from Yusuke Koda's perspective

Ordered by how strongly the researchers Yusuke Koda 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. Gradient-based learning applied to document recognition
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Distilling the Knowledge in a Neural Network (arXiv.org)
10. Going deeper with convolutions

Their papers

• Communication-Efficient Multimodal Split Learning for mmWave Received Power Prediction (2020) — 72 citations
• One Pixel Image and RF Signal Based Split Learning for mmWave Received Power Prediction (2019) — 20 citations
• Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training With Non-IID Private Data (2020) — 379 citations