SinoXiv
2
results found
In the last decades, energy-based models (EBMs) have become an important class of probabilistic models in which a component of the likelihood is intractable and therefore cannot be evaluated explicitl...
Contrastive learning
bridge sampling; reverse logistic regression
multiple importance sampling
binary classification
Imbalanced binary classification is a common issue in serious contexts when rare events have practical effects. Traditional cost-sensitive strategies improve minority identification, but they frequent...
binary classification
imbalanced dataset
cost sensitivity
features selection
mathematical programming
