• DocumentCode
    3643616
  • Title

    Maximization of the information divergence from an exponential family and criticality

  • Author

    František Matúš;Johannes Rauh

  • Author_Institution
    Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Pod vodá
  • fYear
    2011
  • fDate
    7/1/2011 12:00:00 AM
  • Firstpage
    903
  • Lastpage
    907
  • Abstract
    The problem to maximize the information divergence from an exponential family is compared to the maximization of an entropy-like quantity over the boundary of a polytope. First-order conditions on directional derivatives define critical sets for the two problems. The bijection between the sets of global maximizers in the two problems found earlier is extended here to bijections between the sets of local maximizers and the critical sets. This is based on new inequalities relating the maximized quantities and a reformulation of the first order criticality conditions for the second problem.
  • Keywords
    "Atmospheric measurements","Particle measurements","Information theory","Vectors","Neural networks","Calculus"
  • Publisher
    ieee
  • Conference_Titel
    Information Theory Proceedings (ISIT), 2011 IEEE International Symposium on
  • ISSN
    2157-8095
  • Print_ISBN
    978-1-4577-0596-0
  • Electronic_ISBN
    2157-8117
  • Type

    conf

  • DOI
    10.1109/ISIT.2011.6034269
  • Filename
    6034269