L. Kong

Computer Networks and Communications · IEEE Communications Surveys and Tutorials · 2018–2023

A researcher in the Science corpus: 4 papers; trusts 106 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom L. Kong trusts overall

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

  1. Ahmed Alkhateeb
  2. Jonathan Hui
  3. Flavio Bonomi
  4. Diederik P. Kingma
  5. Marko Vukolic
  6. Oscar Novo
  7. Kaiming He
  8. Geoffrey E. Hinton
  9. Mark W. Storer
  10. Li D. Xu

Papers from L. Kong's perspective

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

Their papers