Our pattern theoretic approach to automatic target recognition for infrared scenes combines structured and unstruc-tured representations: rigid, 3-D faceted models for known targets of interest and exible, simply connected shapes to accommodate the unknown \clutterers" that the algorithm may encounter. The radiant intensities of both kinds of targets form nuisance variables which are incorporat...

Clustering is one of the most basic and useful methods of data analysis. This chapter describes a number of powerful clustering models, developed in psychology, for representing objects using data that measure the similarities between pairs of objects. These models place few restrictions on how objects are assigned to clusters, and allow for very general measures of the similarities between obj...

We study parametric unsupervised mixture learning. We measure the loss of intrinsic information from the observations to complex mixture models, and then to simple mixture models. We present a geometric picture, where all these representations are regarded as free points in the space of probability distributions. Based on minimum description length, we derive a simple geometric principle to lea...

Hawkes processes are a special class of temporal point which exhibit natural notion causality, as occurrence events in the past may increase probability future. Discovery underlying influence network among dimensions multi-dimensional is high importance disciplines where high-frequency data to model, e.g. financial or seismological data. This paper approaches problem learning Granger-causal proce...