Hierarchical conceptual clustering has been proven to be a useful data mining technique. Graph-based representation of structural information has been shown to be successful in kn...
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Abstract—We propose a novel search mechanism for unstructured p2p networks, and show that it is both scalable, i.e., it leads to a bounded query traffic load per peer as the pee...
Recent years have seen the development of many graph clustering algorithms, which can identify community structure in networks. The vast majority of these only find disjoint commun...
We study the frugality ratio of truthful mechanisms in path auctions, which measures the extent to which truthful mechanisms “overpay” compared to non-truthful mechanisms. In p...