Husanbir Singh Pannu

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 28 citations into it
• Electrical and Electronic Engineering — 11 citations into it
• Accounting — 7 citations into it
• Information Systems — 7 citations into it

Whom Husanbir Singh Pannu trusts overall

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

1. Nitesh V. Chawla
2. Bartosz Krawczyk
3. Jesse Davis
4. Shuo Wang
5. Rushi Longadge
6. Abeed Sarker
7. Haibo He
8. Sebastián Maldonado
9. Francisco Charte
10. Yuchun Tang

Papers from Husanbir Singh Pannu's perspective

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

1. SMOTE: Synthetic Minority Over-sampling Technique
2. A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches
3. The relationship between Precision-Recall and ROC curves
4. Extreme re-balancing for SVMs: a case study
5. ADASYN: Adaptive synthetic sampling approach for imbalanced learning (IEEE World Congress on Computational Intelligence)
6. Cost-Sensitive Learning of Deep Feature Representations From Imbalanced Data
7. Learning from imbalanced data: open challenges and future directions
8. Classification of Imbalanced Data: a Review (International journal of pattern recognition and artificial intelligence)
9. Discriminative Learning Under Covariate Shift
10. EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling (Pattern Recognition)

Their papers

• A Systematic Review on Imbalanced Data Challenges in Machine Learning (2019) — 683 citations