Chao Huang

Artificial Intelligence · with Lai · 2019

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Chao Huang trusts overall

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

  1. Jerome H. Friedman
  2. Vladimir Naumovich Vapni
  3. Ya-Xiang Yuan
  4. Jasper Snoek
  5. Jane Elith
  6. Richard Perez
  7. R. Mueller
  8. Hugo Larochelle
  9. J. Leathwick
  10. Trevor J. Hastie

Who trusts Chao Huang overall

  1. Billy Pik Lik Lau
  2. Marakkalage Sumudu Hasala

Papers from Chao Huang's perspective

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

  1. The Nature of Statistical Learning Theory
  2. Greedy function approximation: A gradient boosting machine.
  3. Practical Bayesian Optimization of Machine Learning Algorithms
  4. Validation of short and medium term operational solar radiation forecasts in the US
  5. Rethinking satellite-based solar irradiance modelling: The SOLIS clear-sky module
  6. ImageNet classification with deep convolutional neural networks
  7. A working guide to boosted regression trees.
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  10. ImageNet: A large-scale hierarchical image database

Their papers