We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
Classification of items taken from data streams requires algorithms that operate in time sensitive and computationally constrained environments. Often, the available time for class...
Consider a typical recommendation problem. A company has historical records of products sold to a large customer base. These records may be compactly represented as a sparse custom...
Social media forms a central domain for the production and dissemination of real-time information. Even though such flows of information have traditionally been thought of as diffu...