Derek Zhiyuan Cheng

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 4 papers; trusts 28 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 96 citations into it
• Computer Vision and Pattern Recognition — 61 citations into it
• Information Systems — 52 citations into it
• Recommender Systems — 18 citations into it
• Optimization & Training — 13 citations into it
• Model Architectures — 12 citations into it

Whom Derek Zhiyuan Cheng trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Steffen Rendle
5. Yoshua Bengio
6. Ilya Sutskever
7. Alex Krizhevsky
8. Yann LeCun
9. Tomas Mikolov
10. X. Zhang

Who trusts Derek Zhiyuan Cheng overall

1. Junliang Yu

Papers from Derek Zhiyuan Cheng's perspective

Ordered by how strongly the researchers Derek Zhiyuan Cheng 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Sampling-bias-corrected neural modeling for large corpus item recommendations (2019) — 344 citations
• Self-supervised Learning for Large-scale Item Recommendations (2020) — 329 citations
• DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems (2020) — 865 citations
• Learning to Embed Categorical Features without Embedding Tables for Recommendation (2020) — 88 citations