193 search results - page 6 / 39 » Approximate parameter inference in a stochastic reaction-dif... |
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...
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
Abstract— The paper considers the algorithm NLU for distributed (vector) parameter estimation in sensor networks, where, the local observation models are nonlinear, and inter-sen...
NIPS
2007
13 years 8 months ago
2007
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
EMNLP
2010
13 years 5 months ago
2010
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
NIPS
2007
13 years 8 months ago
2007
In many structured prediction problems, the highest-scoring labeling is hard to compute exactly, leading to the use of approximate inference methods. However, when inference is us...