Friday, 15:45 - 16:10 h, Room: MA 313

 

Min Tao
A slightly changed alternating direction method of multipliers for separable convex programming

Coauthors: Sheng Bing He, Ming Xiao Yuan

 

Abstract:
The classical alternating direction method of multiliers (ADMM) has
been well studied in the context of linearly constrained convex
programming and variational inequalities where the involved operator
is formed as the sum of two individual functions without crossed
variables. Recently, ADMM has found many novel applications in
diversified areas such as image processing and statistics. However,
it is still not clear whether ADMM can be extended to the case where
the operator is the sum of more than two individual functions. In
this paper, we present a ADMM with minor change for solving the
linearly constrained separable convex optimization whose involved
operator is separable into three individual functions. The
O(1/t) convergence rate of the proposed methods is
demonstrated.

 

Talk 2 of the invited session Fri.3.MA 313
"Contraction methods for separable convex optimization in the frame of VIs" [...]
Cluster 3
"Complementarity & variational inequalities" [...]

 

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