Cong Xie
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 12 papers; trusts 209 researchers and is trusted by 41 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 158 citations into it; #5,561 of 35,345 by trust here, #7,657 by citations
- Optimization & Training — 118 citations into it; #729 of 2,601 by trust here, #822 by citations
- Computer Vision and Pattern Recognition — 69 citations into it
- Federated & Distributed Learning — 58 citations into it; #81 of 319 by trust here, #158 by citations
- Computer Networks and Communications — 54 citations into it; #1,426 of 9,886 by trust here, #2,539 by citations
- ML Systems & Hardware — 54 citations into it; #161 of 575 by trust here, #312 by citations
- Safety, Robustness & Interpretability — 36 citations into it
- Efficiency & Compression — 29 citations into it
Whom Cong Xie trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Mu Li
- Lili Su
- Sebastian U. Stich
- Yudong Chen
- H. Brendan McMahan
- D. Andersen
- Dong Yin
- Jakub Konecný
- Geoffrey E. Hinton
Who trusts Cong Xie overall
- Oluwasanmi Koyejo
- Indranil Gupta
- Xinyang Cao
- Lie He
- Shashank Rajput
- Sai Praneeth Karimireddy
- Chen Chen
- Virat Shejwalkar
- Hongyi Wang
- El-Mahdi El-Mhamdi
Papers from Cong Xie's perspective
Ordered by how strongly the researchers Cong Xie trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- CSER: Communication-efficient SGD with Error Reset (2020) — 48 citations
- Practical Distributed Learning: Secure Machine Learning with Communication-Efficient Local Updates (2019) — 14 citations
- Zeno++: Robust Fully Asynchronous SGD (2019) — 142 citations
- Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates (2019) — 46 citations
- Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation (2019) — 358 citations
- Asynchronous Federated Optimization (2019) — 771 citations
- SLSGD: Secure and Efficient Distributed On-device Machine Learning (2019) — 62 citations
- Zeno++: robust asynchronous SGD with arbitrary number of Byzantine workers (2019) — 22 citations
- Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance (2018) — 324 citations
- Phocas: dimensional Byzantine-resilient stochastic gradient descent (2018) — 62 citations
- Generalized Byzantine-tolerant SGD (2018) — 304 citations
- Zeno: Byzantine-suspicious stochastic gradient descent (2018) — 48 citations