David R. Cheriton
Artificial Intelligence · 2001–2021
A researcher in the Science corpus: 5 papers; trusts 50 researchers and is trusted by 61 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 31 citations into it; #22,489 of 35,345 by trust here, #14,718 by citations
- Information Retrieval & Search — 25 citations into it; #87 of 1,022 by trust here, #272 by citations
- Information Systems — 19 citations into it
- Computer Networks and Communications — 15 citations into it; #6,431 of 9,886 by trust here, #6,788 by citations
- Computer Vision and Pattern Recognition — 9 citations into it
- Natural Language Processing — 7 citations into it
- Electrical and Electronic Engineering — 6 citations into it; #9,192 of 16,539 by trust here, #14,827 by citations
Whom David R. Cheriton trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Peilin Yang
- Rodrigo Nogueira
- Jacob Devlin
- Jimmy J. Lin
- Sebastian Hofstätter
- Ashish Vaswani
- Noam Shazeer
- Colin Raffel
- Geoffrey E. Hinton
- Kyunghyun Cho
Who trusts David R. Cheriton overall
- Luyu Gao
- Jimmy J. Lin
- Sheng-Chieh Lin
- Jamie Callan
- Jheng-Hong Yang
- Thibault Formal
- Shengyao Zhuang
- Xueguang Ma
- Antonio Mallia
- Zhuyun Dai
Papers from David R. Cheriton's perspective
Ordered by how strongly the researchers David R. Cheriton trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
Their papers
- Pyserini: A Python Toolkit for Reproducible Information Retrieval Research with Sparse and Dense Representations (2021) — 673 citations
- Detecting identity-based attacks in wireless networks using signalprints (2006) — 398 citations
- A Comparison of Document-at-a-Time and Score-at-a-Time Query Evaluation (2017) — 68 citations
- From doc2query to docTTTTTquery (2019)
- An Architecture for Content Routing Support in the Internet (2001) — 313 citations