Jia Hu

Optimization & Training · with Mills · 2020

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 7 citations into it

Whom Jia Hu trusts overall

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

1. H. Brendan McMahan
2. Abhishek V A

Who trusts Jia Hu overall

1. Dinh C. Nguyen
2. Hangyu Zhu
3. Xiaokang Zhou

Papers from Jia Hu's perspective

Ordered by how strongly the researchers Jia Hu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Federated Learning for Mobile Keyboard Prediction
2. Federated Learning of Deep Networks using Model Averaging
3. Federated Learning: Collaborative Machine Learning without Centralized Training Data
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet classification with deep convolutional neural networks
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Dropout: a simple way to prevent neural networks from overfitting
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Communication-Efficient Federated Learning for Wireless Edge Intelligence in IoT (2020) — 383 citations