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ECCV
2008
Springer
14 years 11 months ago
Unsupervised Classification and Part Localization by Consistency Amplification
We present a novel method for unsupervised classification, including the discovery of a new category and precise object and part localization. Given a set of unlabelled images, som...
Leonid Karlinsky, Michael Dinerstein, Dan Levi, Sh...
EMNLP
2007
14 years 11 months ago
Syntactic Re-Alignment Models for Machine Translation
We present a method for improving word alignment for statistical syntax-based machine translation that employs a syntactically informed alignment model closer to the translation m...
Jonathan May, Kevin Knight
COLING
2000
14 years 11 months ago
Language Identification In Unknown Signals
This paper describes algorithms and software developed to characterise and detect generic intelligent language-like features iu an input signal, using Natural Language Learning te...
John R. Elliott, Eric Atwell, Bill Whyte
GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
14 years 10 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
BMCBI
2005
126views more  BMCBI 2005»
14 years 10 months ago
GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA
Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA struc...
Robert G. Beiko, Robert L. Charlebois