Rushi Longadge

Artificial Intelligence · 2013

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Rushi Longadge trusts overall

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

  1. Michael Wasikowski
  2. Xue-wen Chen
  3. Nitesh V. Chawla

Who trusts Rushi Longadge overall

  1. Harsurinder Kaur
  2. Sara Fotouhi
  3. Matloob Khushi
  4. Shahrokh Asadi
  5. Husanbir Singh Pannu
  6. Xun Cheng
  7. Kamran Shaukat
  8. Michael W. Kattan
  9. Avleen Kaur Malhi
  10. Gabriele Macari

Papers from Rushi Longadge's perspective

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

  1. Combating the Small Sample Class Imbalance Problem Using Feature Selection (IEEE Transactions on Knowledge and Data Engineering)
  2. A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches
  3. Mining with rarity: a unifying framework
  4. SMOTE: Synthetic Minority Over-sampling Technique
  5. MetaCost: a general method for making classifiers cost-sensitive
  6. SMOTEBoost: Improving Prediction of the Minority Class in Boosting
  7. Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction (Journal of Artificial Intelligence Research)
  8. The Foundations of Cost-Sensitive Learning
  9. Feature selection for text categorization on imbalanced data (SKDD)
  10. One-Class SVMs for Document Classification (Journal of machine learning research)

Their papers