Masaru Todoriki

Graph Learning · 2018

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

Subfields

• Graph Learning — 8 citations into it

Whom Masaru Todoriki trusts overall

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

1. Karsten M. Borgwardt
2. Nino Shervashidze
3. Sergey Ioffe
4. Tamara G. Kolda
5. Geoffrey E. Hinton
6. Xavier Glorot
7. Evrim Acar
8. Nitish Srivastava
9. Yoshua Bengio
10. Marco Tulio Ribeiro

Papers from Masaru Todoriki's perspective

Ordered by how strongly the researchers Masaru Todoriki trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Dropout: a simple way to prevent neural networks from overfitting
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• Learning Multi-Way Relations via Tensor Decomposition With Neural Networks (2018) — 27 citations