Jui-Ting Huang

Artificial Intelligence · 2012–2014

A researcher in the Science corpus: 5 papers; trusts 42 researchers and is trusted by 73 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 84 citations into it; #3,215 of 35,345 by trust here, #3,175 by citations
• Signal Processing — 65 citations into it; #634 of 7,572 by trust here, #352 by citations
• Speech & Audio — 27 citations into it; #670 of 1,076 by trust here, #535 by citations
• Natural Language Processing — 20 citations into it; #2,480 of 5,688 by trust here, #1,377 by citations
• Computer Vision and Pattern Recognition — 12 citations into it
• Model Architectures — 8 citations into it; #799 of 2,278 by trust here, #1,111 by citations
• Efficiency & Compression — 6 citations into it; #378 of 1,264 by trust here, #633 by citations

Whom Jui-Ting Huang trusts overall

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

1. Dong Yu
2. Li Deng
3. Geoffrey E. Hinton
4. George E. Dahl
5. R. Caruana
6. Brian Kingsbury
7. Abdel-rahman Mohamed
8. Yoshua Bengio
9. Tara N. Sainath
10. Ronan Collobert

Who trusts Jui-Ting Huang overall

1. Li Deng
2. Jinyu Li
3. Dong Yu
4. Sylvestre-Alvise Rebuffi
5. Dong Wang
6. Takaaki Hori
7. Zhong Meng
8. Vimal Manohar
9. Yongxin Yang
10. Yajie Miao

Papers from Jui-Ting Huang's perspective

Ordered by how strongly the researchers Jui-Ting Huang 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Learning small-size DNN with output-distribution-based criteria (2014) — 311 citations
• Cross-language knowledge transfer using multilingual deep neural network with shared hidden layers (2013) — 686 citations
• Recent advances in deep learning for speech research at Microsoft (2013) — 820 citations
• Feature Learning in Deep Neural Networks - A Study on Speech Recognition Tasks (2013) — 266 citations
• Improving wideband speech recognition using mixed-bandwidth training data in CD-DNN-HMM (2012) — 147 citations