138 search results - page 11 / 28 » Inferring Hidden Causal Structure |
Publication
A key goal for the perceptual system is to optimally combine
information from all the senses that may be available in order to
develop the most accurate and unified picture possi...
UAI
1998
13 years 11 months ago
1998
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
CVPR
2007
IEEE
14 years 11 months ago
2007
IEEE
We present a generative model approach to explore intrinsic semantic structures in sport videos, e.g., the camera view in American football games. We will invoke the concept of se...
UAI
2008
13 years 11 months ago
2008
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
UAI
2008
13 years 11 months ago
2008
An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used ...