Xiaoqin Zhang
Reinforcement Learning · with Ma · 2017–2018
A researcher in the Science corpus: 2 papers; trusts 62 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 28 citations into it
- Artificial Intelligence — 25 citations into it
- Management Science and Operations Research — 6 citations into it
- Computational Theory and Mathematics — 5 citations into it
- Control and Systems Engineering — 5 citations into it
- Electrical and Electronic Engineering — 5 citations into it
Whom Xiaoqin Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Andrew Y. Ng
- Diederik P. Kingma
- David Silver
- Pieter Abbeel
- Volodymyr Mnih
- Geoffrey E. Hinton
- Sham M. Kakade
- Nicolas Manfred Otto Heess
- Jonathan Ho
Who trusts Xiaoqin Zhang overall
Papers from Xiaoqin Zhang's perspective
Ordered by how strongly the researchers Xiaoqin Zhang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)