29 citations · 35 across the 6 of their papers we have counts for
6 papers
Hankel low-rank approximation and completion in time series analysis and forecasting: a brief review
Jonathan Gillard, Konstantin Usevich
In this paper we offer a review and bibliography of work on Hankel low-rank approximation and completion, with particular emphasis on how this methodology can be used for time seri…
Segmentation analysis and the recovery of queuing parameters via the Wasserstein distance: a study of administrative data for patients with chronic obstructive pulmonary disease
Henry Wilde, Vincent Knight, Jonathan Gillard +1
This work uses a data-driven approach to analyse how the resource requirements of patients with chronic obstructive pulmonary disease (COPD) may change, quantifying how those chang…
A novel initialisation based on hospital-resident assignment for the k-modes algorithm
Henry Wilde, Vincent Knight, Jonathan Gillard
This paper presents a new way of selecting an initial solution for the k-modes algorithm that allows for a notion of mathematical fairness and a leverage of the data that the commo…
Evolutionary Dataset Optimisation: learning algorithm quality through evolution
Henry Wilde, Vincent Knight, Jonathan Gillard
In this paper we propose a novel method for learning how algorithms perform. Classically, algorithms are compared on a finite number of existing (or newly simulated) benchmark data…
Recognising and evaluating the effectiveness of extortion in the Iterated Prisoner's Dilemma
Vincent A. Knight, Marc Harper, Nikoleta E. Glynatsi +1
Since the introduction of zero-determinant strategies, extortionate strategies have received considerable interest. While an interesting class of strategies, the definitions of ext…
Structured low-rank matrix completion for forecasting in time series analysis
Jonathan Gillard, Konstantin Usevich
In this paper we consider the low-rank matrix completion problem with specific application to forecasting in time series analysis. Briefly, the low-rank matrix completion problem i…