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» A maximum entropy approach to species distribution modeling
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CVPR
2003
IEEE
14 years 10 months ago
An Efficient Approach to Learning Inhomogeneous Gibbs Model
Inhomogeneous Gibbs model (IGM) [4] is an effective maximum entropy model in characterizing complex highdimensional distributions. However, its training process is so slow that th...
Ziqiang Liu, Hong Chen, Heung-Yeung Shum
BMCBI
2005
118views more  BMCBI 2005»
13 years 7 months ago
Vestige: Maximum likelihood phylogenetic footprinting
Background: Phylogenetic footprinting is the identification of functional regions of DNA by their evolutionary conservation. This is achieved by comparing orthologous regions from...
Matthew J. Wakefield, Peter Maxwell, Gavin A. Hutt...
WSC
2004
13 years 9 months ago
Global Likelihood Optimization Via the Cross-Entropy Method, with an Application to Mixture Models
Global likelihood maximization is an important aspect of many statistical analyses. Often the likelihood function is highly multi-extremal. This presents a significant challenge t...
Zdravko I. Botev, Dirk P. Kroese
PPSN
1994
Springer
14 years 1 days ago
An Evolutionary Algorithm for Integer Programming
Abstract. The mutation distribution of evolutionary algorithms usually is oriented at the type of the search space. Typical examples are binomial distributions for binary strings i...
Günter Rudolph
ICCV
2001
IEEE
14 years 10 months ago
Learning Inhomogeneous Gibbs Model of Faces by Minimax Entropy
In this paper we propose a novel inhomogeneous Gibbs model by the minimax entropy principle, and apply it to face modeling. The maximum entropy principle generalizes the statistic...
Ce Liu, Song Chun Zhu, Heung-Yeung Shum