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A Graphical Model for Evolutionary Optimization

Evolutionary Computation, 2008
We present a statistical model of empirical optimization that admits the creation of algorithms with explicit and intuitively defined desiderata. Because No Free Lunch theorems dictate that no optimization algorithm can be considered more efficient than any other when considering all possible functions, the desired function class plays a prominent ...
Christopher K. Monson, Kevin D. Seppi
openaire   +2 more sources

Discrete Graphical Models and Their Parameterization

2018
This chapter is devoted to graphical models in which the observed variables are categorical, that is, whose state space consists of a finite number of values. The focus is on regression graph models, because this family of models allows us to approach discrete graphical models with a sufficient degree of generality.
La Rocca, Luca, Roverato, Alberto
openaire   +2 more sources

Graphical Modelling

1995
Abstract The aim of this chapter is to provide a non-technical overview of graphical modelling. Independence graphs with both lines (undirected edges) and arrows (directed edges) are described, together with associated models in duding both discrete and continuous variables. Some discussion of causal inference is also given. Graphical
openaire   +1 more source

Joint Gaussian graphical model estimation: A survey

Wiley Interdisciplinary Reviews: Computational Statistics, 2022
Mladen Kolar   +2 more
exaly  

Image Segmentation with a Unified Graphical Model

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010
Qiang Ji
exaly  

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