This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
A fundamental assumption for any machine learning task is to have training and test data instances drawn from the same distribution while having a sufficiently large number of tra...
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
Extracting sentiments from unstructured text has emerged as an important problem in many disciplines. An accurate method would enable us, for example, to mine online opinions from ...
We use the data collected by the Lung Image Database Consortium (LIDC) for modeling the radiologists’ nodule interpretations based on image content of the nodule by using decisi...
Ekarin Varutbangkul, Vesna Mitrovic, Daniela Stan ...