Masashi Takeshita

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it
• Natural Language Processing — 12 citations into it
• Safety, Robustness & Interpretability — 12 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Masashi Takeshita trusts overall

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

1. Tomas Mikolov
2. Geoffrey E. Hinton
3. L. V. D. van der Maaten
4. Yoav Benjamini
5. Hila Gonen
6. David Arthur
7. Ilya Sutskever
8. Piotr Bojanowski
9. Tianlu Wang
10. Yoshua Bengio

Papers from Masashi Takeshita's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Can Existing Methods Debias Languages Other than English? First Attempt to Analyze and Mitigate Japanese Word Embeddings (2020)