Yanghua Peng
Artificial Intelligence · 2018–2024
A researcher in the Science corpus: 4 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 85 citations into it
- Computer Vision and Pattern Recognition — 50 citations into it
- Optimization & Training — 34 citations into it
- Efficiency & Compression — 30 citations into it
- Model Architectures — 16 citations into it
Whom Yanghua Peng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Karen Simonyan
- Ilya Sutskever
- X. Zhang
- Yoshua Bengio
- Diederik P. Kingma
- Yann LeCun
- Andrew Zisserman
Who trusts Yanghua Peng overall
- Youhui Bai
- Peifeng Yu
- Zhihao Bai
- Mosharaf Chowdhury
- Yimin Jiang
- Cheng Li
- Da Zheng
- Zhen Zhang
- Yibo Zhu
Papers from Yanghua Peng's perspective
Ordered by how strongly the researchers Yanghua Peng trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- A generic communication scheduler for distributed DNN training acceleration (2019) — 407 citations
- MegaScale: Scaling Large Language Model Training to More Than 10, 000 GPUs (2024) — 350 citations
- HybridFlow: A Flexible and Efficient RLHF Framework (2024) — 2,000 citations
- Optimus: an efficient dynamic resource scheduler for deep learning clusters (2018) — 511 citations