Suzan Köknar-Tezel

Artificial Intelligence

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Suzan Köknar-Tezel trusts overall

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

  1. Vladimir Naumovich Vapni
  2. Nitesh V. Chawla
  3. Rehan Akbani
  4. Kevin W. Bowyer
  5. L. Hall
  6. Stephen Kwek
  7. Nathalie Japkowicz
  8. Aleksandar Lazarevic
  9. Gary M. Weiss
  10. Radford M. Neal

Who trusts Suzan Köknar-Tezel overall

  1. Faisal Kamiran
  2. Toon Calders
  3. Indrė Žliobaitė

Papers from Suzan Köknar-Tezel's perspective

Ordered by how strongly the researchers Suzan Köknar-Tezel trusts endorse each paper. Same corpus, a different order for every researcher.

  1. SMOTE: Synthetic Minority Over-sampling Technique
  2. The Nature of Statistical Learning Theory
  3. SMOTEBoost: Improving Prediction of the Minority Class in Boosting
  4. Applying Support Vector Machines to Imbalanced Datasets (European Conference on Machine Learning)
  5. Robust Classification for Imprecise Environments
  6. The Class Imbalance Problem: Significance and Strategies
  7. Evaluating boosting algorithms to classify rare classes: comparison and improvements (Proceedings 2001 IEEE International Conference on Data Mining)
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. Fast Effective Rule Induction
  10. Special Invited Paper-Additive logistic regression: A statistical view of boosting

Their papers