Harsurinder Kaur

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 Harsurinder Kaur 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 Harsurinder Kaur's perspective

Ordered by how strongly the researchers Harsurinder Kaur 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. The relationship between Precision-Recall and ROC curves
5. Extreme re-balancing for SVMs: a case study
6. Gradient-based learning applied to document recognition
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. ADASYN: Adaptive synthetic sampling approach for imbalanced learning (IEEE World Congress on Computational Intelligence)
9. The use of the area under the ROC curve in the evaluation of machine learning algorithms
10. Cost-Sensitive Learning of Deep Feature Representations From Imbalanced Data

Their papers

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