Jiechao Xiong
Reinforcement Learning · 2014–2018
A researcher in the Science corpus: 4 papers; trusts 38 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 74 citations into it
- Artificial Intelligence — 65 citations into it
- Optimization & Training — 18 citations into it
- Management Science and Operations Research — 14 citations into it
- Statistics and Probability — 14 citations into it
- Computational Mechanics — 11 citations into it
- Control and Systems Engineering — 8 citations into it
- Economics and Econometrics — 7 citations into it
Whom Jiechao Xiong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- John Schulman
- Volodymyr Mnih
- David Silver
- Ronald J. Williams
- Sham M. Kakade
- Sergey Levine
- Geoffrey E. Hinton
- Andrew Barto
- Koray Kavukcuoglu
Who trusts Jiechao Xiong overall
Papers from Jiechao Xiong's perspective
Ordered by how strongly the researchers Jiechao Xiong 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Reinforcement Learning: An Introduction
Their papers
- TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game (2018) — 78 citations
- Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space (2018) — 240 citations
- Exponentially Weighted Imitation Learning for Batched Historical Data (2018) — 143 citations
- Sparse Recovery via Differential Inclusions (2014) — 77 citations