Frontiers

Stochastic undersampling steepens auditory threshold/duration functions: implications for understanding auditory deafferentation and aging

It has long been known that some listeners experience hearing difficulties out of proportion with their audiometric losses. Notably, some older adults as well as auditory neuropathy patients have ...
GitHub

Hashing-Based Undersampling Ensemble for Imbalanced Pattern Classification Problems

Undersampling is a popular method to solve imbalanced classification problems. However, sometimes it may remove too many majority samples which may lead to loss of informative samples. In this article ...
Frontiers

Why do I hear but not understand? Stochastic undersampling as a model of degraded neural encoding of speech

Hearing impairment is a serious disease with increasing prevalence. It is defined based on increased audiometric thresholds but increased thresholds are only partly responsible for the greater ...
GitHub

Undersampling is a Minimax Optimal Robustness Intervention in Nonparametric Classification

@article{chatterji2022undersampling, title={Undersampling is a Minimax Optimal Robustness Intervention in Nonparametric Classification}, author={Chatterji, Niladri S and Haque, Saminul and Hashimoto, ...
IEEE

Exploratory Undersampling for Class-Imbalance Learning

Abstract: Undersampling is a popular method in dealing with class-imbalance problems, which uses only a subset of the majority class and thus is very efficient. The main deficiency is that many ...
IEEE

Diversified Sensitivity-Based Undersampling for Imbalance Classification Problems

Abstract: Undersampling is a widely adopted method to deal with imbalance pattern classification problems. Current methods mainly depend on either random resampling on the majority class or resampling ...