Eunjeong Jeong
Artificial Intelligence · 2018–2019
A researcher in the Science corpus: 3 papers; trusts 4 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 20 citations into it; #23,674 of 35,345 by trust here, #10,430 by citations
- Electrical and Electronic Engineering — 6 citations into it; #11,097 of 16,539 by trust here, #5,871 by citations
Whom Eunjeong Jeong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jihong Park
- H. Brendan McMahan
- Geoffrey E. Hinton
- Mehdi Mirza
- Robin C. Geyer
- Simon Osindero
- Eider Moore
- Rohan Anil
- Medhi Bennis
- Yue Zhao
Who trusts Eunjeong Jeong overall
- Jihong Park
- Anis Elgabli
- Medhi Bennis
- Hong-You Chen
- Zhuangdi Zhu
- Jinhyun Ahn
- Sumudu Samarakoon
- Omar Abdel Wahab
- Tao Lin
- Hong Chang
Papers from Eunjeong Jeong's perspective
Ordered by how strongly the researchers Eunjeong Jeong 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Distilling the Knowledge in a Neural Network (arXiv.org)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data (2018) — 759 citations
- Distilling On-Device Intelligence at the Network Edge (2019) — 33 citations
- Multi-hop Federated Private Data Augmentation with Sample Compression (2019) — 19 citations