Georgios Douzas

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 23 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it; #12,634 of 35,345 by trust here, #21,878 by citations
• Electrical and Electronic Engineering — 12 citations into it; #11,480 of 16,539 by trust here, #14,379 by citations
• Statistics and Probability — 8 citations into it
• Evaluation & Benchmarks — 7 citations into it
• Accounting — 6 citations into it
• Information Systems — 6 citations into it
• Statistical Learning Theory — 6 citations into it

Whom Georgios Douzas trusts overall

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

1. Nitesh V. Chawla
2. Foster J. Provost
3. Jaka Demsar
4. Haibo He
5. David Sculley
6. Taeho C. Jo
7. Nathalie Japkowicz
8. David A. Cieslak
9. Chumphol Bunkhumpornpat
10. Pedro M. Domingos

Who trusts Georgios Douzas overall

1. Justin Engelmann
2. Adamu Ali-Gombe
3. Mingle Xu
4. Fei Wang
5. Stefan Lessmann
6. Eyad Elyan
7. Sook Yoon
8. Azal Ahmad Khan
9. Eugene Bagdasarian
10. Dhiraj Neupane

Papers from Georgios Douzas's perspective

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

1. SMOTE: Synthetic Minority Over-sampling Technique
2. Statistical Comparisons of Classifiers over Multiple Data Sets
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet classification with deep convolutional neural networks
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Editorial: special issue on learning from imbalanced data sets
8. Learning Multiple Layers of Features from Tiny Images
9. The Nature of Statistical Learning Theory
10. Long Short-Term Memory

Their papers

• Oversampling for Imbalanced Learning Based on K-Means and SMOTE (2017) — 940 citations
• Effective data generation for imbalanced learning using conditional generative adversarial networks (2018) — 576 citations