K. Hamidieh

Computational materials science · 2018

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

Whom K. Hamidieh trusts overall

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

  1. Jerome H. Friedman
  2. Robert E. Schapire
  3. Tianqi Chen
  4. Robert P. Sheridan
  5. Valentin G. Stanev
  6. Carlos Guestrin
  7. David Ruppert
  8. Alan J. Izenman
  9. Corey Oses
  10. Andy Liaw

Papers from K. Hamidieh's perspective

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

  1. Greedy function approximation: A gradient boosting machine.
  2. The Strength of Weak Learnability
  3. ImageNet classification with deep convolutional neural networks
  4. Gradient-based learning applied to document recognition
  5. Regression Shrinkage and Selection via the Lasso
  6. XGBoost: A Scalable Tree Boosting System
  7. The Elements of Statistical Learning: Data Mining, Inference, and Prediction
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers