Jonathan Gillard | DeepAI

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∙ 06/10/2022

Hankel low-rank approximation and completion in time series analysis and forecasting: a brief review

In this paper we offer a review and bibliography of work on Hankel low-r...

0 Jonathan Gillard, et al. ∙

∙ 08/10/2020

Segmentation analysis and the recovery of queuing parameters via the Wasserstein distance: a study of administrative data for patients with chronic obstructive pulmonary diseas

This work uses a data-driven approach to analyse how the resource requir...

0 Henry Wilde, et al. ∙

∙ 04/04/2020

Generic probabilistic modelling and non-homogeneity issues for the UK epidemic of COVID-19

Coronavirus COVID-19 spreads through the population mostly based on soci...

0 Anatoly Zhigljavsky, et al. ∙

∙ 02/07/2020

A novel initialisation based on hospital-resident assignment for the k-modes algorithm

This paper presents a new way of selecting an initial solution for the k...

0 Henry Wilde, et al. ∙

∙ 07/31/2019

Evolutionary Dataset Optimisation: learning algorithm quality through evolution

In this paper we propose a new method for learning how algorithms perfor...

0 Henry Wilde, et al. ∙

∙ 04/01/2019

Recognising and evaluating the effectiveness of extortion in the Iterated Prisoner's Dilemma

Since the introduction of zero-determinant strategies, extortionate stra...

0 Vincent A. Knight, et al. ∙

∙ 02/22/2018

Structured low-rank matrix completion for forecasting in time series analysis

In this paper we consider the low-rank matrix completion problem with sp...

0 Jonathan Gillard, et al. ∙

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