When a dataset from a non-negative random variable contains zero or very small observations, the folded-normal distribution (FND) can be an appropriate model for fitting the data. Such data includes ...

To solve this problem, we propose a framework based on the maximum classifier discrepancy with marginal probability distribution adaptation that focuses on task-specific decision boundaries.