We propose an efficient algorithm for principal component analysis (PCA) that is applicable when only the inner product with a given vector is needed. We show that Krylov subspace...
Background: Within the emerging field of text mining and statistical natural language processing (NLP) applied to biomedical articles, a broad variety of techniques have been deve...
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
are proposing a model to help organizations detect and prevent cheats in online assessments. First we analyze different student personalities, stress situations generated by onlin...
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...