Yukihiro Tagami
Artificial Intelligence · 2017–2018
A researcher in the Science corpus: 2 papers; trusts 48 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 32 citations into it; #19,434 of 35,345 by trust here, #21,878 by citations
- Computer Vision and Pattern Recognition — 24 citations into it
- Information Systems — 22 citations into it; #3,992 of 8,771 by trust here, #4,012 by citations
- Representation & Self-Supervised Learning — 15 citations into it
- Recommender Systems — 10 citations into it
- Model Architectures — 7 citations into it
- Natural Language Processing — 6 citations into it
Whom Yukihiro Tagami trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Ilya Sutskever
- Geoffrey E. Hinton
- Pascal Vincent
- Ruslan Salakhutdinov
- Diederik P. Kingma
- Quoc V. Le
- Alex Krizhevsky
- Tomas Mikolov
- Oriol Vinyals
Who trusts Yukihiro Tagami overall
Papers from Yukihiro Tagami's perspective
Ordered by how strongly the researchers Yukihiro Tagami trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Cross-domain Recommendation via Deep Domain Adaptation (2018) — 99 citations
- Embedding-based News Recommendation for Millions of Users (2017) — 502 citations