759 search results - page 13 / 152 » Structured Learning with Approximate Inference |
CORR
2012
Springer
12 years 3 months ago
2012
Springer
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
IJCAI
2001
13 years 8 months ago
2001
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
NIPS
2004
13 years 8 months ago
2004
We propose a novel a framework for deriving approximations for intractable probabilistic models. This framework is based on a free energy (negative log marginal likelihood) and ca...
TIP
2008
13 years 7 months ago
2008
This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...
ECML
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...