Tao Hu

with Zhang · 2017

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

Whom Tao Hu trusts overall

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

  1. Jerome H. Friedman

Papers from Tao Hu's perspective

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

  1. Greedy function approximation: A gradient boosting machine.
  2. Boosting Algorithms as Gradient Descent
  3. Predicting Taxi–Passenger Demand Using Streaming Data (IEEE transactions on intelligent transportation systems (Print))
  4. Bagging Predictors
  5. Experiments with a New Boosting Algorithm
  6. Prediction Games and Arcing Algorithms
  7. The Nature of Statistical Learning Theory
  8. An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization
  9. Improved Boosting Algorithms Using Confidence-rated Predictions
  10. Regression Shrinkage and Selection via the Lasso

Their papers