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    TSP
    2008
    139views more  TSP 2008»
    Bayesian Filtering With Random Finite Set Observations
    13 years 4 months ago
    Bayesian Filtering With Random Finite Set Observations
    Download  www.ee.uwa.edu.au
    This paper presents a novel and mathematically rigorous Bayes recursion for tracking a target that generates multiple measurements with state dependent sensor field of view and clu...
    Ba-Tuong Vo, Ba-Ngu Vo, Antonio Cantoni
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    TIP
    2008
    133views more  TIP 2008»
    A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields
    13 years 5 months ago
    A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields
    Download  projects.csail.mit.edu
    This paper presents recursive cavity modeling--a principled, tractable approach to approximate, near-optimal inference for large Gauss-Markov random fields. The main idea is to su...
    Jason K. Johnson, Alan S. Willsky
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    IJCAI
    2007
    148views Artificial Intelligence» more  IJCAI 2007»
    Recursive Random Fields
    13 years 6 months ago
    Recursive Random Fields
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    A formula in first-order logic can be viewed as a tree, with a logical connective at each node, and a knowledge base can be viewed as a tree whose root is a conjunction. Markov l...
    Daniel Lowd, Pedro Domingos
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    NIPS
    2008
    185views Information Technology» more  NIPS 2008»
    Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
    13 years 6 months ago
    Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
    Download  www.computing.edu.au
    Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
    Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
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    CVPR
    2005
    IEEE
    283views Computer Vision» more  CVPR 2005»
    A Dynamic Conditional Random Field Model for Object Segmentation in Image Sequences
    14 years 7 months ago
    A Dynamic Conditional Random Field Model for Object Segmentation in Image Sequences
    Download  people.ee.duke.edu
    This paper presents a dynamic conditional random field (DCRF) model to integrate contextual constraints for object segmentation in image sequences. Spatial and temporal dependenci...
    Qiang Ji, Yang Wang 0002
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