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We consider the point-to-point lossy coding for computing and channel codingproblems with two-sided information. We first unify these problems byconsidering a new generalized problem. Then we develop graph-basedcharacterizations and derive interesting reductions through explicit graphoperations, which reduce the number of decision variables. After that, wedesign alternating optimization algorithms for the unified problems, so thatnumerical computations for both the source and channel problems are covered.With the help of extra root-finding techniques, proper multiplier updatestrategies are developed. Thus our algorithms can compute the problems for agiven distortion or cost constraint and the convergence can be proved. Also,extra heuristic deflation techniques are introduced which largely reduce thecomputational time. Numerical results show the accuracy and efficiency of ouralgorithms.

A Graph-Based Approach to the Computation of Rate-Distortion and Capacity-Cost Functions with Side Information