Rui Zhao
Artificial Intelligence · with Li · 2014–2017
A researcher in the Science corpus: 3 papers; trusts 44 researchers and is trusted by 21 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 54 citations into it; #7,704 of 35,345 by trust here, #9,170 by citations
- Signal Processing — 47 citations into it; #1,246 of 7,572 by trust here, #1,120 by citations
- Speech & Audio — 23 citations into it; #916 of 1,076 by trust here, #996 by citations
- Natural Language Processing — 15 citations into it
- Efficiency & Compression — 9 citations into it; #379 of 1,264 by trust here, #633 by citations
- Model Architectures — 8 citations into it; #800 of 2,278 by trust here, #1,111 by citations
- Computer Vision and Pattern Recognition — 6 citations into it
Whom Rui Zhao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Graves
- Li Deng
- Dong Yu
- Yoshua Bengio
- Jinyu Li
- George E. Dahl
- Jimmy Ba
- Andrew W. Senior
- Navdeep Jaitly
Who trusts Rui Zhao overall
- Jinyu Li
- Liang Lu
- Zhong Meng
- Dong Yu
- Gakuto Kurata
- Zhuo Chen
- Dong Wang
- Yoon Kim
- Shaoshi Ling
- Haiyan Yin
Papers from Rui Zhao's perspective
Ordered by how strongly the researchers Rui Zhao trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
Their papers
- Learning small-size DNN with output-distribution-based criteria (2014) — 311 citations
- Large-Scale Domain Adaptation via Teacher-Student Learning (2017) — 142 citations
- Improved training for online end-to-end speech recognition systems (2017) — 47 citations