James Sanger

Artificial Intelligence · 2006

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Natural Language Processing — 20 citations into it

Whom James Sanger trusts overall

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

1. Thorsten Joachims
2. Yiming Yang

Who trusts James Sanger overall

1. Ronen Feldman
2. Lili Mou
3. Luca Maria Aiello

Papers from James Sanger's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Attention is All you Need (Neural Information Processing Systems)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data (2006) — 804 citations