Chenxu Zhu

Artificial Intelligence · 2020–2023

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 83 citations into it
• Information Systems — 46 citations into it
• Computer Vision and Pattern Recognition — 31 citations into it
• Recommender Systems — 10 citations into it
• Model Architectures — 6 citations into it

Whom Chenxu Zhu trusts overall

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

1. Steffen Rendle
2. Sergey Ioffe
3. Xiangnan He
4. Yehuda Koren

Papers from Chenxu Zhu's perspective

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

1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction (2020) — 206 citations
• How Can Recommender Systems Benefit from Large Language Models: A Survey (2023) — 404 citations