Shoujin Wang

Information Systems · 2016–2019

A researcher in the Science corpus: 3 papers; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Information Systems — 72 citations into it
• Artificial Intelligence — 59 citations into it
• Management Science and Operations Research — 27 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Recommender Systems — 13 citations into it
• Model Architectures — 7 citations into it

Whom Shoujin Wang trusts overall

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

1. Balázs Hidasi
2. Alexandros Karatzoglou
3. Massimo Quadrana
4. Yoshua Bengio
5. Dietmar Jannach
6. Tomas Mikolov
7. Geoffrey E. Hinton
8. Malte Ludewig
9. Steffen Rendle
10. Tom Fawcett

Who trusts Shoujin Wang overall

1. Adamu Ali-Gombe
2. M. M. Afsar
3. Qi Dong
4. Sajad Mousavi
5. Elnaz Lashgari
6. Lixu Wang
7. Ziyang Wang
8. Eyad Elyan
9. Trafford Crump
10. Shaogang Gong

Papers from Shoujin Wang's perspective

Ordered by how strongly the researchers Shoujin Wang 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. Long Short-Term Memory
4. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Training deep neural networks on imbalanced data sets (2016) — 452 citations
• Sequential Recommender Systems: Challenges, Progress and Prospects (2019) — 517 citations
• A Survey on Session-based Recommender Systems (2019) — 614 citations