Seunghye Lee

Civil and Structural Engineering · 2004–2021

A researcher in the Science corpus: 4 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Seunghye Lee trusts overall

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

  1. Leo Breiman
  2. Robert E. Schapire
  3. Brian Uy
  4. Hanchuan Peng
  5. Jerome H. Friedman
  6. Thomas G. Dietterich
  7. Fuhui Long

Papers from Seunghye Lee's perspective

Ordered by how strongly the researchers Seunghye Lee 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. Bagging Predictors
  4. Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
  5. Multiple Classifier Systems
  6. CatBoost: unbiased boosting with categorical features (Neural Information Processing Systems)
  7. Machine learning-based compressive strength prediction for concrete: An adaptive boosting approach (Construction and Building Materials)
  8. Axial performance of short concrete filled steel tubes with high- and ultra-high- strength materials
  9. Strength of short concrete filled high strength steel box columns
  10. Mechanics of Composite Materials with MATLAB

Their papers