A Dual Optimization Framework for Some Problems of Information Theory and Statistics.

Abstract

A new dual optimization framework for some problems of information theory and statistics is developed in the form of dual convex programming problems and their duality theory. It extends the work for finite discrete distributions to the case of general measures. Although the primal problem (constrained relative entropy) is an infinite dimensional one, the dual problem is a finite dimensional one without constraints and involving only exponential and linear terms. Applications range from mathematical statistics and statistical mechanics to traffic engineering, marketing and economics.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1977
Accession Number
ADA055155

Entities

People

  • A. Ben-tal
  • Abraham Charnes

Organizations

  • University of Texas at Austin

Tags

DTIC Thesaurus Topics

  • Banach Space
  • Convex Programming
  • Convex Sets
  • Discrete Distribution
  • Economics
  • Engineering
  • Functional Analysis
  • Information Theory
  • Integrals
  • Mechanics
  • New York
  • Optimization
  • Probability
  • Statistical Mechanics
  • Statistics
  • Stochastic Processes
  • Theorems

Fields of Study

  • Mathematics

Readers

  • Operations Research
  • Theoretical Analysis.