We present a simple and scalable graph clustering method called power iteration clustering (PIC). PIC finds a very low-dimensional embedding of a dataset using truncated power ite...
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
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...
Classification with only one labeled example per class is a challenging problem in machine learning and pattern recognition. While there have been some attempts to address this pr...
Web pages are more than text and they contain much contextual and structural information, e.g., the title, the meta data, the anchor text, etc., each of which can be seen as a dat...