Hongzhao Huang

Artificial Intelligence · 2015–2019

A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 49 citations into it; #28,602 of 35,345 by trust here, #15,236 by citations
• Natural Language Processing — 32 citations into it; #4,730 of 5,688 by trust here, #4,539 by citations
• Representation & Self-Supervised Learning — 9 citations into it
• Information Systems — 7 citations into it

Whom Hongzhao Huang trusts overall

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

1. Silviu Cucerzan
2. Antoine Bordes
3. Yoshua Bengio
4. David N. Milne
5. Geoffrey E. Hinton
6. Jason Aaron Edward Weston
7. Ronan Collobert
8. Richard Socher
9. Diederik P. Kingma
10. Xiaojin Zhu

Who trusts Hongzhao Huang overall

1. Gintare Karolina Dziugaite
2. Nicola De Cao
3. Zheng Fang
4. Sidharth Mudgal
5. Daniel M. Roy
6. Gautier Izacard
7. Yanan Cao
8. Phong Le
9. Octavian-Eugen Ganea

Papers from Hongzhao Huang's perspective

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

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

Their papers

• Transformer-Based Acoustic Modeling for Hybrid Speech Recognition (2019) — 266 citations
• Leveraging Deep Neural Networks and Knowledge Graphs for Entity Disambiguation (2015) — 93 citations