438 citations · 875 across the 77 of their papers we have counts for
4 papers · 2 filters
First order online optimisation using forward gradients in over-parameterised systems
Behnam Mafakheri, Iman Shames, Jonathan H. Manton
The success of deep learning over the past decade mainly relies on gradient-based optimisation and backpropagation. This paper focuses on analysing the performance of first-order g…
Global convergence and asymptotic optimality of the heavy ball method for a class of non-convex optimization problems
Valery Ugrinovskii, Ian R. Petersen, Iman Shames
In this letter we revisit the famous heavy ball method and study its global convergence for a class of non-convex problems with sector-bounded gradient. We characterize the paramet…
Online Convex Optimization Using Coordinate Descent Algorithms
Yankai Lin, Iman Shames, Dragan Nešić
This paper considers the problem of online optimization where the objective function is time-varying. In particular, we extend coordinate descent type algorithms to the online case…
Gradient Free Cooperative Seeking of a Moving Source
Elad Michael, Chris Manzie, Tony A. Wood +2
In this paper, we consider the optimisation of a time varying scalar field by a network of agents with no gradient information. We propose a composite control law, blending extremu…