On the convergence of the proximal point algorithm for convex minimization
SIAM Journal on Control and Optimization
A fast Legendre transform algorithm and applications to the adhesion model
Journal of Scientific Computing
SIAM Journal on Numerical Analysis
A fast computational algorithm for the Legendre-Fenchel transform
Computational Optimization and Applications
Fast Euclidean distance transformation in two scans using a 3 × 3 neighborhood
Computer Vision and Image Understanding
A Linear Euclidean Distance Transform Algorithm Based on the Linear-Time Legendre Transform
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Symbolic computation of Fenchel conjugates
ACM Communications in Computer Algebra
Mathematical Programming: Series A and B - Nonlinear convex optimization and variational inequalities
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A new computational framework for computer-aided convex analysis is proposed and investigated. Existing computational frameworks are reviewed and their limitations pointed out. The class of piecewise linear-quadratic functions is introduced to improve convergence and stability. A stable convex calculus is achieved using symbolic-numeric algorithms to compute all fundamental transforms of convex analysis. Our main result states the existence of efficient (linear time) algorithms for the class of piecewise linear-quadratic functions. We also recall that such class is closed under convex transforms. We illustrate the results with numerical examples, and validate numerically the resulting computational framework.