The problem of learning tree-structured Gaussian graphical models from independent and identically distributed (i.i.d.) samples is considered. The influence of the tree structure a...
Vincent Y. F. Tan, Animashree Anandkumar, Alan S. ...
Network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. Many algorithms find clusters by maximizing the number of i...
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, Thomas A. J...
Abstract There is an intimate link between program structure and behaviour. Exploiting this link to phrase program correctness problems in terms of the structural properties of a p...
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
The problem of indexing path queries in semistructured/XML databases has received considerable attention recently, and several proposals have advocated the use of structure indexe...
Raghav Kaushik, Philip Bohannon, Jeffrey F. Naught...