Hongyang Yang

Reinforcement Learning · 2020–2023

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

Subfields

• Reinforcement Learning — 14 citations into it
• Finance — 5 citations into it

Whom Hongyang Yang trusts overall

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

1. John Schulman
2. Jason C. Hsu
3. Tim Dettmers
4. Volodymyr Mnih
5. Richard S. Sutton
6. Geoffrey E. Hinton
7. J. Edward Hu
8. Diederik P. Kingma
9. Yoshua Bengio
10. Sergey Levine

Who trusts Hongyang Yang overall

1. M. A. Ganaie
2. Minghui Hu

Papers from Hongyang Yang's perspective

Ordered by how strongly the researchers Hongyang Yang 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Deep reinforcement learning for automated stock trading: an ensemble strategy (2020) — 317 citations
• FinGPT: Open-Source Financial Large Language Models (2023) — 434 citations