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 ...

Abstract: This paper focuses on a Byzantine-robust distributed stochastic non-convex optimization problem with smooth local cost functions over unbalanced networks. In particular, the nodes in a ...

Abstract: Optimality and computational efficiency are two very desirable but also competitive attributes of optimal feed planning. A well-designed algorithm can vastly increase machining productivity ...

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 competitive economy equilibrium computation. We show that, for the first time, the equilibrium sets of the following two markets: 1. A mixed Fisher and Arrow-Debreu market with homogeneous ...

We study non-convex delayed-noise online optimization problems by evaluating dynamic regret in the non-stationary setting when the loss functions are quasar-convex. In particular, we consider ...