Xinwei Zhang

Artificial Intelligence · with Liu · 2019–2022

A researcher in the Science corpus: 5 papers; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 87 citations into it
• Federated & Distributed Learning — 42 citations into it
• Optimization & Training — 35 citations into it
• Computational Mechanics — 24 citations into it
• ML Systems & Hardware — 10 citations into it
• Management Science and Operations Research — 7 citations into it
• Electrical and Electronic Engineering — 6 citations into it

Whom Xinwei Zhang trusts overall

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

1. Yurii E. Nesterov
2. Hao Yu
3. Sebastian U. Stich
4. Tian Li
5. Anit Kumar Sahu
6. H. Brendan McMahan
7. Peter Richtárik
8. Haoran Sun
9. Sen Yang
10. Jakub Konecný

Who trusts Xinwei Zhang overall

1. Yae Jee Cho
2. Jianyu Wang
3. Yang Liu

Papers from Xinwei Zhang's perspective

Ordered by how strongly the researchers Xinwei Zhang 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. Gradient-based learning applied to document recognition
4. Learning Multiple Layers of Features from Tiny Images
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Attention is All you Need (Neural Information Processing Systems)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• FedBCD: A Communication-Efficient Collaborative Learning Framework for Distributed Features (2022) — 139 citations
• Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention (2020) — 39 citations
• FedPD: A Federated Learning Framework With Adaptivity to Non-IID Data (2020) — 286 citations
• A Communication Efficient Vertical Federated Learning Framework (2019) — 79 citations
• A Communication Efficient Collaborative Learning Framework for Distributed Features (2019) — 62 citations