Yu Hasegawa

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 Yu Hasegawa trusts

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

1. Karsten M. Borgwardt (in Graph Learning)

Papers from Yu Hasegawa's perspective

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

1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
2. Dropout: a simple way to prevent neural networks from overfitting
3. Deep Sparse Rectifier Neural Networks
4. Human-level concept learning through probabilistic program induction
5. Tensor Decompositions and Applications
6. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
7. Shortest-path kernels on graphs
8. Marginalized Kernels Between Labeled Graphs
9. Association for Computational Linguistics " Why Should I Trust You? " Explaining the Predictions of Any Classifier
10. Efficient graphlet kernels for large graph comparison

Their papers

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