Tuong Le

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Tuong Le trusts overall

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

  1. Gustavo E. A. P. A. Batista
  2. Guillaume Lemaitre
  3. Flavio Luiz de Moraes Barboza
  4. Jorma Laurikkala
  5. Tom Fawcett
  6. Yoav Freund
  7. Maciej Ziȩba
  8. Hui Han
  9. Ronaldo Cristiano Prati
  10. Fernando Nogueira

Who trusts Tuong Le overall

  1. Dang Lien Minh
  2. Abolghasem Sadeghi-Niaraki
  3. Huynh Duc Huy

Papers from Tuong Le's perspective

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

  1. SMOTE: Synthetic Minority Over-sampling Technique
  2. Borderline-SMOTE: A New Over-Sampling Method in Imbalanced Data Sets Learning
  3. A decision-theoretic generalization of on-line learning and an application to boosting
  4. A study of the behavior of several methods for balancing machine learning training data
  5. ADASYN: Adaptive synthetic sampling approach for imbalanced learning (IEEE World Congress on Computational Intelligence)
  6. Improving Identification of Difficult Small Classes by Balancing Class Distribution (Conference on Artificial Intelligence in Medicine in Europe)
  7. Scikit-learn: Machine Learning in Python
  8. An introduction to ROC analysis
  9. An instance level analysis of data complexity (Machine-mediated learning)
  10. Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning

Their papers