Zuozhu Liu

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 41 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it; #20,421 of 35,345 by trust here, #14,438 by citations
• Natural Language Processing — 32 citations into it
• Computer Networks and Communications — 18 citations into it
• Representation & Self-Supervised Learning — 17 citations into it
• Electrical and Electronic Engineering — 16 citations into it; #6,982 of 16,539 by trust here, #8,322 by citations
• Computer Vision and Pattern Recognition — 12 citations into it
• Optimization & Training — 11 citations into it
• Evaluation & Benchmarks — 9 citations into it

Whom Zuozhu Liu trusts overall

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

1. Martin Haenggi
2. Eneko Agirre
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Richard Socher
6. Guangxu Zhu
7. Diederik P. Kingma
8. Howard H. Yang
9. Alex Krizhevsky
10. Daniel Matthew Cer

Who trusts Zuozhu Liu overall

1. Mingzhe Chen
2. Zhaohui Yang
3. Khaled Ben Letaief
4. Walid Saad

Papers from Zuozhu Liu's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• An Unsupervised Sentence Embedding Method by Mutual Information Maximization (2020) — 197 citations
• Scheduling Policies for Federated Learning in Wireless Networks (2019) — 590 citations