Yixin Cao

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 7 papers; trusts 94 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 141 citations into it; #11,033 of 35,345 by trust here, #6,468 by citations
• Information Systems — 103 citations into it; #2,450 of 8,771 by trust here, #1,158 by citations
• Computer Vision and Pattern Recognition — 56 citations into it
• Recommender Systems — 30 citations into it
• Management Science and Operations Research — 28 citations into it
• Model Architectures — 19 citations into it
• Natural Language Processing — 19 citations into it
• Representation & Self-Supervised Learning — 18 citations into it

Whom Yixin Cao trusts overall

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

1. Xiangnan He
2. Steffen Rendle
3. Yoshua Bengio
4. Diederik P. Kingma
5. Geoffrey E. Hinton
6. Antoine Bordes
7. Julian McAuley
8. Alex Krizhevsky
9. Ilya Sutskever
10. Yehuda Koren

Who trusts Yixin Cao overall

1. Xiang Wang
2. Xiangnan He
3. Qingyu Guo
4. Yin-wei Wei
5. Tat-seng Chua
6. Xiaowen Huang
7. Zequn Sun
8. Le Wu
9. Xu Chen
10. Tinglin Huang

Papers from Yixin Cao's perspective

Ordered by how strongly the researchers Yixin Cao 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. 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets (2018) — 664 citations
• KGAT: Knowledge Graph Attention Network for Recommendation (2019) — 2,302 citations
• Multi-Channel Graph Neural Network for Entity Alignment (2019) — 302 citations
• Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences (2019) — 695 citations
• Personalized Fashion Recommendation with Visual Explanations based on Multimodal Attention Network: Towards Visually Explainable Recommendation (2019) — 358 citations
• Sequential Recommendation with User Memory Networks (2018) — 544 citations
• Visually Explainable Recommendation (2018) — 54 citations