Jun He

IEEE Sensors Journal · with Sun · 2017

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Jun He trusts

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

1. Tin Kam Ho (in Optimization & Training)
2. Leo Breiman (in Evaluation & Benchmarks)

Papers from Jun He's perspective

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

1. Bagging Predictors
2. Random Forests
3. The Random Subspace Method for Constructing Decision Forests
4. Statistical learning theory
5. Shape Quantization and Recognition with Randomized Trees
6. Boosting the margin: A new explanation for the effectiveness of voting methods
7. Arcing classifier (with discussion and a rejoinder by the author)
8. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants
9. Experiments with a New Boosting Algorithm
10. Consistent Nonparametric Regression

Their papers

• Fault Diagnosis of a Rolling Bearing Using Wavelet Packet Denoising and Random Forests (2017) — 310 citations