Although prediction models for delirium, a commonly occurring condition
...
An applied problem facing all areas of data science is harmonizing data
...
Data quality is a common problem in machine learning, especially in
high...
With the current ongoing debate about fairness, explainability and
trans...
We use Generative Adversarial Networks (GANs) to design a class conditio...
For feature selection and related problems, we introduce the notion of
c...
We consider the problem of learning linear classifiers when both feature...
In binary classification framework, we are interested in making cost
sen...