In applications such as fraud and intrusion detection, it is of great interest to measure the evolving trends in the data. We consider the problem of quantifying changes between tw...
A challenging problem of multi-label learning is that both the label space and the model complexity will grow rapidly with the increase in the number of labels, and thus makes the...
While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooper...
Sandra Zilles, Steffen Lange, Robert Holte, Martin...
We consider the problem of selecting a subset of m most informative features where m is the number of required features. This feature selection problem is essentially a combinator...
Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, ...
A classical approach in multi-class pattern classification is the following. Estimate probability distributions that generated the observations for each label class, and then labe...