Lingjing Kong

Artificial Intelligence · 2020

A researcher in the Science corpus: 2 papers; trusts 80 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 85 citations into it; #23,736 of 35,345 by trust here, #15,542 by citations
• Computer Vision and Pattern Recognition — 50 citations into it
• Efficiency & Compression — 27 citations into it
• Optimization & Training — 18 citations into it
• Representation & Self-Supervised Learning — 14 citations into it
• Meta & Continual Learning — 12 citations into it
• Model Architectures — 11 citations into it
• Radiology, Nuclear Medicine and Imaging — 8 citations into it

Whom Lingjing Kong trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yann LeCun
5. Yoshua Bengio
6. Max Welling
7. Ilya Sutskever
8. Diederik P. Kingma
9. Karen Simonyan
10. X. Zhang

Who trusts Lingjing Kong overall

1. Yue Tan
2. Mang Ye
3. Zhuangdi Zhu
4. Fei Mi
5. Qinbin Li
6. Wenke Huang
7. Chaoyang He
8. Guodong Long
9. Elahe Arani
10. Hangyu Zhu

Papers from Lingjing Kong's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Ensemble Distillation for Robust Model Fusion in Federated Learning (2020) — 1,521 citations
• Generalized Class Incremental Learning (2020) — 48 citations