We address the problem of learning topic hierarchies from data. The model selection problem in this domain is daunting—which of the large collection of possible trees to use? We...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...
Performance modeling is important for the purpose of developing efficient dimensioning tools for large complicated networks. But it is difficult to achieve in heterogeneous wireles...
With the increase of amount of transistors which can be contained on a chip and the constant expectation for more sophisticated applications, the design of Systems-on-Chip (SoC) is...
The robust operation of many sensor network applications depends on deploying relays to ensure wireless coverage. Radio mapping aims to predict network coverage based on a small n...
We introduce mixture trees, a tree-based data-structure for modeling joint probability densities using a greedy hierarchical density estimation scheme. We show that the mixture tr...