Convex optimisation constitutes a fundamental area in applied mathematics where the objective is to identify the minimum of a convex function subject to a set of convex constraints. This framework ...

Letian YI, Siyuan YANG, Ying CUI, and Zhilu LAI (2025). Transforming Physics-Informed Machine Learning to Convex Optimization. Physics-Informed Machine Learning (PIML) offers a powerful paradigm of ...

In this paper, we aim to find ecient solutions of a multi-objective optimization problem over a linear matrix inequality (LMI in short), in which the objective functions are SOS-convex polynomials. We ...

In this note, we extend the algorithms Extra [13] and subgradient-push [10] to a new algorithm ExtraPush for consensus optimization with convex differentiable objective functions over a directed ...

We study a class of optimization problems motivated by automating the design and update of AI systems like coding assistants, robots, and copilots. AutoDiff frameworks, like PyTorch, enable efficient ...

Abstract: In this article, a method has been established for optimizing multivariate nonlinear discontinuous cost functions having multiple simple kinks in their domains of definition, by applying ...

Abstract: In this work, we focus on solving non-smooth non-convex maximization problems in multi-group multicast transmission. By leveraging Karush-Kuhn-Tucker (KKT) optimality conditions, we ...