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» Using Parsimony to Guide Maximum Likelihood Searches
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ISBI
2011
IEEE
14 years 1 months ago
Hippocampus segmentation using a stable maximum likelihood classifier ensemble algorithm
We develop a new algorithm to segment the hippocampus from MR images. Our method uses a new classifier ensemble algorithm to correct segmentation errors produced by a multi-atlas...
Hongzhi Wang, Jung Wook Suh, Sandhitsu R. Das, Mur...
VTC
2006
IEEE
115views Communications» more  VTC 2006»
15 years 3 months ago
Suboptimal Maximum Likelihood Detection Using Gradient-based Algorithm for MIMO Channels
Abstract— This paper proposes a suboptimal maximum likelihood detection (MLD) algorithm for multiple-input multipleoutput (MIMO) communications. The proposed algorithm regards tr...
Thet Htun Khine, Kazuhiko Fukawa, Hiroshi Suzuki
BIBM
2008
IEEE
134views Bioinformatics» more  BIBM 2008»
15 years 3 months ago
New Approaches to Compare Phylogenetic Search Heuristics
We present new and novel insights into the behavior of two maximum parsimony heuristics for building evolutionary trees of different sizes. First, our results show that the heuris...
Seung-Jin Sul, Suzanne Matthews, Tiffani L. Willia...
ICC
2007
IEEE
150views Communications» more  ICC 2007»
15 years 3 months ago
Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems
— Blind and semiblind adaptive schemes are proposed for joint maximum likelihood (ML) channel estimation and data detection for multiple-input multiple-output (MIMO) systems. The...
Mohammed Abuthinien, Sheng Chen, Andreas Wolfgang,...
GECCO
2005
Springer
150views Optimization» more  GECCO 2005»
15 years 2 months ago
A GA for maximum likelihood phylogenetic inference using neighbour-joining as a genotype to phenotype mapping
Evolutionary relationships among species can be represented by a phylogenetic tree and inferred by optimising some measure of fitness, such as the statistical likelihood of the t...
Leon Poladian