8 search results - page 1 / 2 » Variable module graphs: a framework for inference and learni... |
ICIP
2005
IEEE
14 years 6 months ago
2005
IEEE
We present a novel and intuitive framework for building modular vision systems for complex tasks such as surveillance applications. Inspired by graphical models, especially factor...
IAT
2009
IEEE
13 years 8 months ago
2009
IEEE
Abstract--This paper is focusing on exact Bayesian reasoning in systems of agents, which represent weakly coupled processing modules supporting collaborative inference through mess...
ICTAI
2009
IEEE
13 years 11 months ago
2009
IEEE
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...
ECCV
2006
Springer
14 years 6 months ago
2006
Springer
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
JMLR
2010
12 years 11 months ago
2010
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...