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    PAMI
    2010
    205views more  PAMI 2010»
    Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
    13 years 6 months ago
    Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
    Download  www.stat.ucla.edu
    In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
    Long Zhu, Yuanhao Chen, Alan L. Yuille
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    COGSCI
    2010
    125views more  COGSCI 2010»
    A Probabilistic Computational Model of Cross-Situational Word Learning
    13 years 8 months ago
    A Probabilistic Computational Model of Cross-Situational Word Learning
    Download  www.coli.uni-saarland.de
    Words are the essence of communication: they are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisiti...
    Afsaneh Fazly, Afra Alishahi, Suzanne Stevenson
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    IJCNN
    2007
    IEEE
    222views Neural Networks» more  IJCNN 2007»
    Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
    14 years 2 months ago
    Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
    Download  theoval.cmp.uea.ac.uk
    Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
    Gavin C. Cawley, Nicola L. C. Talbot
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    BMCBI
    2010
    159views more  BMCBI 2010»
    Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
    13 years 8 months ago
    Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
    Download  www.biomedcentral.com
    Background: Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods ha...
    Alvaro J. González, Li Liao
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    AIEDAM
    1998
    87views more  AIEDAM 1998»
    Learning to set up numerical optimizations of engineering designs
    13 years 8 months ago
    Learning to set up numerical optimizations of engineering designs
    Download  ti.arc.nasa.gov
    Gradient-based numerical optimization of complex engineering designs offers the promise of rapidly producing better designs. However, such methods generally assume that the object...
    Mark Schwabacher, Thomas Ellman, Haym Hirsh
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