We introduce tiered clustering, a mixture model capable of accounting for varying degrees of shared (context-independent) feature structure, and demonstrate its applicability to i...
The paper presents a novel coding technique based on approximate geometry for images taken from arbitrary recording positions around a 3-D scene. Such data structures occur in ima...
We develop a framework to detect when certain sounds are present in a mixed audio signal. We focus on the regime where out of a large number of possible sounds, a small but unknow...
This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...