228 search results - page 11 / 46 » Large Deviation Methods for Approximate Probabilistic Infere... |
ICCV
2001
IEEE
14 years 9 months ago
2001
IEEE
Tree-structured probabilistic models admit simple, fast inference. However, they are not well suited to phenomena such as occlusion, where multiple components of an object may dis...
ESOP
2011
Springer
12 years 11 months ago
2011
Springer
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
IJCAI
2003
13 years 8 months ago
2003
We present a new general framework for online istic plan recognition called the Abstract Hidden Markov Memory Model (AHMEM). The l is an extension of the existing Abstract Hidden ...
ORL
2006
13 years 7 months ago
2006
In this paper we derive estimates of the sample sizes required to solve a multistage stochastic programming problem with a given accuracy by the (conditional sampling) sample aver...
IJON
2010
13 years 2 months ago
2010
This paper presents a novel methodology to infer parameters of probabilistic models whose output noise is a Student-t distribution. The method is an extension of earlier work for ...