Bias-Corrected Data Synthesis for Imbalanced Learning
stat.ML, cs.LG, stat.ME
Submitted: 2025-10-30
Updated: 2026-09-11
Comments: 44 pages, 4 figures, includes proofs and appendix
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Concentration and excess risk bounds for imbalanced classification with synthetic oversampling
- Revisit the Imbalance Optimization in Multi-task Learning: An Experimental Analysis
- Auto-Encoding Variational Bayes
- Flow Matching for Generative Modeling
- Machine Learning for Synthetic Data Generation: A Review
- An Empirical Analysis of the Efficacy of Different Sampling Techniques for Imbalanced Classification
- Score-Based Generative Modeling through Stochastic Differential Equations
- Conditional Data Synthesis Augmentation
- Classification Imbalance as Transfer Learning
- mixup: Beyond Empirical Risk Minimization
- How Does Mixup Help With Robustness and Generalization?
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