Caihong Zeng
Artificial Intelligence · 2019
A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 26 citations into it
- Computer Vision and Pattern Recognition — 16 citations into it
- Safety, Robustness & Interpretability — 12 citations into it
- Privacy & Security — 10 citations into it
Whom Caihong Zeng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Caihong Zeng's perspective
Ordered by how strongly the researchers Caihong Zeng trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Dropout: a simple way to prevent neural networks from overfitting
- Understanding deep learning requires rethinking generalization
- ImageNet classification with deep convolutional neural networks
- Deep Learning with Differential Privacy
- Regularization of Neural Networks using DropConnect
- Gradient-based learning applied to document recognition
- Differentially Private Empirical Risk Minimization