Li Chen
Artificial Intelligence · with Chen · 2019
A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 16 citations into it
- Computer Vision and Pattern Recognition — 8 citations into it
- Federated & Distributed Learning — 7 citations into it
- Optimization & Training — 7 citations into it
Whom Li Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Boris Polyak
- Ning Qian
- Yann LeCun
- H. Brendan McMahan
- Alex Krizhevsky
- Shancang Li
- Yoshua Bengio
- L. Eon Bottou
- Geoffrey E. Hinton
- Shiqiang Wang
Who trusts Li Chen overall
- Chaouki Ben Issaid
- Omar Abdel Wahab
- Dinh C. Nguyen
- Anis Elgabli
- Azzam Mourad
- George Pu
- Ming Ding
- Yanlin Zhou
- Jihong Park
Papers from Li Chen's perspective
Ordered by how strongly the researchers Li Chen trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- 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
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Accelerating Federated Learning via Momentum Gradient Descent (2019) — 346 citations