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    JAIR
    2010
    111views more  JAIR 2010»
    Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language
    14 years 8 months ago
    Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language
    Download  www.cs.utexas.edu
    We present a novel framework for learning to interpret and generate language using only perceptual context as supervision. We demonstrate its capabilities by developing a system t...
    David L. Chen, Joohyun Kim, Raymond J. Mooney
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    CVPR
    2008
    IEEE
    196views Computer Vision» more  CVPR 2008»
    Recognition by association via learning per-exemplar distances
    16 years 1 days ago
    Recognition by association via learning per-exemplar distances
    Download  www.cs.cmu.edu
    We pose the recognition problem as data association. In this setting, a novel object is explained solely in terms of a small set of exemplar objects to which it is visually simila...
    Tomasz Malisiewicz, Alexei A. Efros
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    CVPR
    2008
    IEEE
    222views Computer Vision» more  CVPR 2008»
    Structure-perceptron learning of a hierarchical log-linear model
    16 years 1 days ago
    Structure-perceptron learning of a hierarchical log-linear model
    Download  people.csail.mit.edu
    In this paper, we address the problems of deformable object matching (alignment) and segmentation with cluttered background. We propose a novel hierarchical log-linear model (HLLM...
    Long Zhu, Yuanhao Chen, Xingyao Ye, Alan L. Yuille
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    ATAL
    2006
    Springer
    138views Intelligent Agents» more  ATAL 2006»
    Learning a common language through an emergent interaction topology
    15 years 1 months ago
    Learning a common language through an emergent interaction topology
    Download  staff.vbi.vt.edu
    We study the effects of various emergent topologies of interaction on the rate of language convergence in a population of communicating agents. The agents generate, parse, and lea...
    Samarth Swarup, Kiran Lakkaraju, Les Gasser
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    ACL
    2007
    125views Computational Linguistics» more  ACL 2007»
    A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity
    14 years 11 months ago
    A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity
    Download  www.dfki.de
    A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as...
    Feiyu Xu, Hans Uszkoreit, Hong Li
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