Yuyang Deng
Artificial Intelligence · 2020
A researcher in the Science corpus: 1 paper; trusts 32 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 45 citations into it; #24,628 of 35,345 by trust here, #18,186 by citations
- Federated & Distributed Learning — 24 citations into it; #218 of 319 by trust here, #237 by citations
- Optimization & Training — 15 citations into it
- Representation & Self-Supervised Learning — 6 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it
- Meta & Continual Learning — 5 citations into it
Whom Yuyang Deng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- L. Eon Bottou
- Mehryar Mohri
- Shai Ben-David
- Shai Shalev-Shwartz
- Yishay Mansour
- Sai Praneeth Karimireddy
- Sebastian U. Stich
- Geoffrey E. Hinton
- Chelsea Finn
- Farzin Haddadpour
Who trusts Yuyang Deng overall
- Yutao Huang
- Canh T. Dinh
- Liam Collins
- Michael Zhang
- Lingyang Chu
- Aryan Mokhtari
- Jaehoon Oh
- Nguyen H. Tran
- Guodong Long
- Zirui Zhou
Papers from Yuyang Deng's perspective
Ordered by how strongly the researchers Yuyang Deng 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Adaptive Personalized Federated Learning (2020) — 710 citations