This paper addresses the problem of learning from highly structured data. Speci cally, it describes a procedure, called decomposition, that allows a learner to access automatically...
Coordinated data structures are sets of (perhaps unbounded) data structures where the nodes of each structure may share types with the corresponding nodes of the other structures....
Abstract. A method for measuring the density of data sets that contain an unknown number of clusters of unknown sizes is proposed. This method, called Pareto Density Estimation (PD...
Background: The unsupervised discovery of structures (i.e. clusterings) underlying data is a central issue in several branches of bioinformatics. Methods based on the concept of s...
In this article we propose a new hashing framework for tree-structured data. Our method maps an unordered tree into a multiset of simple wedge-shaped structures refered to as pivot...