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math.OC2026

Differential estimates for fast first-order multilevel nonconvex optimisation

Neil Dizon, Tuomo Valkonen

With a view on bilevel and PDE-constrained optimisation, we develop iterative estimates of for composite functions , where is the…

math.OC2026

Convergent Lifted Lasserre Hierarchy of SDPs for Minimizing Expectation of Piecewise Polynomial Loss over Wasserstein Balls

N. D. Dizon, Q. Y. Huang, T. D. Chuong +2

This paper investigates the minimization of the expectation of piecewise polynomial loss functions over Wasserstein balls. This optimization problem often appears as a key sub-prob…

math.OC2026

Interwoven SDP in Primal-Dual Proximal Splitting Methods for Adjustable Robust Convex Optimisation with SOS-Convex Polynomial Constraints

Neil D. Dizon, Bethany I. Caldwell, Vaithilingam Jeyakumar +1

We propose a novel methodology for solving a two-stage adjustable robust convex optimisation problem with a general (proximable) convex objective function and constraints defined b…

math.OC2025

Online optimisation for dynamic electrical impedance tomography

Neil Dizon, Jyrki Jauhiainen, Tuomo Valkonen

Online optimisation studies the convergence of optimisation methods as the data embedded in the problem changes. Based on this idea, we propose a primal dual online method for nonl…

math.OC2024

Prediction techniques for dynamic imaging with online primal-dual methods

Neil Dizon, Jyrki Jauhiainen, Tuomo Valkonen

Online optimisation facilitates the solution of dynamic inverse problems, such as image stabilisation, fluid flow monitoring, and dynamic medical imaging. In this paper, we improve…