362 citations · 470 across the 35 of their papers we have counts for
7 papers · 1 filter
Fast and robust consensus-based optimization via optimal feedback control
Yuyang Huang, Michael Herty, Dante Kalise +1
We propose a variant of consensus-based optimization (CBO) algorithms, controlled-CBO, which introduces a feedback control term to improve convergence towards global minimizers of…
Scalarisation-based risk concepts for robust multi-objective optimisation
Ben Tu, Nikolas Kantas, Robert M. Lee +1
Robust optimisation is a well-established framework for optimising functions in the presence of uncertainty. The inherent goal of this problem is to identify a collection of inputs…
Multi-objective optimisation via the R2 utilities
Ben Tu, Nikolas Kantas, Robert M. Lee +1
The goal of multi-objective optimisation is to identify a collection of points which describe the best possible trade-offs between the multiple objectives. In order to solve this v…
Stochastic Mirror Descent for Convex Optimization with Consensus Constraints
Anastasia Borovykh, Nikolas Kantas, Panos Parpas +1
The mirror descent algorithm is known to be effective in situations where it is beneficial to adapt the mirror map to the underlying geometry of the optimization model. However, th…
Joint Online Parameter Estimation and Optimal Sensor Placement for the Partially Observed Stochastic Advection-Diffusion Equation
Louis Sharrock, Nikolas Kantas
In this paper, we consider the problem of jointly performing online parameter estimation and optimal sensor placement for a partially observed infinite dimensional linear diffusion…
Two-Timescale Stochastic Gradient Descent in Continuous Time with Applications to Joint Online Parameter Estimation and Optimal Sensor Placement
Louis Sharrock, Nikolas Kantas
In this paper, we establish the almost sure convergence of two-timescale stochastic gradient descent algorithms in continuous time under general noise and stability conditions, ext…