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    BMVC
    1997
    98views Computer Vision» more  BMVC 1997»
    Employing Region Features for Searching an Image Database
    13 years 11 months ago
    Employing Region Features for Searching an Image Database
    Download  www.cs.bris.ac.uk
    This paper describes recent work on the use of regional data extracted from segmented images for use as search keys in an image database query system. The motivation for this work...
    Matthew E. J. Wood, Neill W. Campbell, Barry T. Th...
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    NIPS
    2000
    198views Information Technology» more  NIPS 2000»
    Learning Joint Statistical Models for Audio-Visual Fusion and Segregation
    13 years 11 months ago
    Learning Joint Statistical Models for Audio-Visual Fusion and Segregation
    Download  www.eecs.berkeley.edu
    People can understand complex auditory and visual information, often using one to disambiguate the other. Automated analysis, even at a lowlevel, faces severe challenges, includin...
    John W. Fisher III, Trevor Darrell, William T. Fre...
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    AAAI
    1994
    117views Intelligent Agents» more  AAAI 1994»
    Control Strategies for a Stochastic Planner
    13 years 11 months ago
    Control Strategies for a Stochastic Planner
    Download  alumnus.caltech.edu
    We present new algorithms for local planning over Markov decision processes. The base-level algorithm possesses several interesting features for control of computation, based on s...
    Jonathan Tash, Stuart J. Russell
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    ACL
    1996
    115views Computational Linguistics» more  ACL 1996»
    Generating an LTAG out of a Principle-based Hierarchical Representation
    13 years 11 months ago
    Generating an LTAG out of a Principle-based Hierarchical Representation
    Download  www.aclweb.org
    Lexicalized Tree Adjoining Grammars have proved useful for NLP. However, numerous redundancy problems face LTAGs developers, as highlighted by Vijay-Shanker and Schabes (92). We p...
    Marie-Hélène Candito
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    UAI
    1996
    151views Artificial Intelligence» more  UAI 1996»
    Learning Equivalence Classes of Bayesian Network Structures
    13 years 11 months ago
    Learning Equivalence Classes of Bayesian Network Structures
    Download  jmlr.csail.mit.edu
    Two Bayesian-network structures are said to be equivalent if the set of distributions that can be represented with one of those structures is identical to the set of distributions...
    David Maxwell Chickering
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