• DocumentCode
    2482618
  • Title

    Tensor Power Method for Efficient MAP Inference in Higher-order MRFs

  • Author

    Semenovich, Dimitri ; Sowmya, Arcot

  • Author_Institution
    Univ. of New South Wales, Sydney, NSW, Australia
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    734
  • Lastpage
    737
  • Abstract
    We present a new efficient algorithm for maximizing energy functions with higher order potentials suitable for MAP inference in discrete MRFs. Initially we relax integer constraints on the problem and obtain potential label assignments using higher-order (tensor) power method. Then we utilise an ascent procedure similar to the classic ICM algorithm to converge to a solution meeting the original integer constraints.
  • Keywords
    Markov processes; inference mechanisms; maximum likelihood estimation; random processes; tensors; MAP inference; discrete MRF; higher-order tensor power method; integer constraints; tensor power method; Approximation algorithms; Approximation methods; Belief propagation; Inference algorithms; Manganese; Markov processes; Tensile stress; Belief Propagation; Higher Order Power Method; MAP inference; MRF;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.185
  • Filename
    5596033
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2482618