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Estimating Dynamic Graphical Models from Multivariate Time-Series Data: Recent Methods and Results

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Estimating Dynamic Graphical Models from Multivariate Time-Series Data: Recent Methods and Results. / Gibberd, A. J.; Nelson, J. D. B.
Advanced Analysis and Learning on Temporal Data: First ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015, Revised Selected Papers. ed. / Ahlame Douzal-Chouakria; José A. Vilar; Pierre-François Marteau. Cham: Springer International Publishing AG, 2016. p. 111-128.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Gibberd, AJ & Nelson, JDB 2016, Estimating Dynamic Graphical Models from Multivariate Time-Series Data: Recent Methods and Results. in A Douzal-Chouakria, JA Vilar & P-F Marteau (eds), Advanced Analysis and Learning on Temporal Data: First ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015, Revised Selected Papers. Springer International Publishing AG, Cham, pp. 111-128. https://doi.org/10.1007/978-3-319-44412-3_8

APA

Gibberd, A. J., & Nelson, J. D. B. (2016). Estimating Dynamic Graphical Models from Multivariate Time-Series Data: Recent Methods and Results. In A. Douzal-Chouakria, J. A. Vilar, & P-F. Marteau (Eds.), Advanced Analysis and Learning on Temporal Data: First ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015, Revised Selected Papers (pp. 111-128). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-44412-3_8

Vancouver

Gibberd AJ, Nelson JDB. Estimating Dynamic Graphical Models from Multivariate Time-Series Data: Recent Methods and Results. In Douzal-Chouakria A, Vilar JA, Marteau P-F, editors, Advanced Analysis and Learning on Temporal Data: First ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015, Revised Selected Papers. Cham: Springer International Publishing AG. 2016. p. 111-128 Epub 2016 Aug 4. doi: 10.1007/978-3-319-44412-3_8

Author

Gibberd, A. J. ; Nelson, J. D. B. / Estimating Dynamic Graphical Models from Multivariate Time-Series Data : Recent Methods and Results. Advanced Analysis and Learning on Temporal Data: First ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015, Revised Selected Papers. editor / Ahlame Douzal-Chouakria ; José A. Vilar ; Pierre-François Marteau. Cham : Springer International Publishing AG, 2016. pp. 111-128

Bibtex

@inproceedings{2f9beccf6b8f4e09a44de3e916941c9b,
title = "Estimating Dynamic Graphical Models from Multivariate Time-Series Data: Recent Methods and Results",
abstract = "Dynamic graphical models aim to describe the time-varying dependency structure of multiple time-series. In this article we review research focusing on the formulation and estimation of such models. The bulk of work in graphical structurelearning problems has focused in the stationary i.i.d setting, we present a brief overview of this work before introducing some dynamic extensions. In particular we focuson two classes of dynamic graphical model; continuous (smooth) models which are estimated via localised kernels, and piecewise models utilising regularisation based estimation. We give an overview of theoretical and empirical results regarding these models, before demonstrating their qualitative difference in the context of a real-world financial time-series dataset. We conclude with a discussion of the state of the field and future research directions.",
keywords = "Graphical model, Sparsity, Changepoint, Time-series, Dynamics, Regularization",
author = "Gibberd, {A. J.} and Nelson, {J. D. B.}",
year = "2016",
doi = "10.1007/978-3-319-44412-3_8",
language = "English",
isbn = "9783319444123",
pages = "111--128",
editor = "Ahlame Douzal-Chouakria and Vilar, {Jos{\'e} A.} and Pierre-Fran{\c c}ois Marteau",
booktitle = "Advanced Analysis and Learning on Temporal Data: First ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015, Revised Selected Papers",
publisher = "Springer International Publishing AG",
address = "Switzerland",

}

RIS

TY - GEN

T1 - Estimating Dynamic Graphical Models from Multivariate Time-Series Data

T2 - Recent Methods and Results

AU - Gibberd, A. J.

AU - Nelson, J. D. B.

PY - 2016

Y1 - 2016

N2 - Dynamic graphical models aim to describe the time-varying dependency structure of multiple time-series. In this article we review research focusing on the formulation and estimation of such models. The bulk of work in graphical structurelearning problems has focused in the stationary i.i.d setting, we present a brief overview of this work before introducing some dynamic extensions. In particular we focuson two classes of dynamic graphical model; continuous (smooth) models which are estimated via localised kernels, and piecewise models utilising regularisation based estimation. We give an overview of theoretical and empirical results regarding these models, before demonstrating their qualitative difference in the context of a real-world financial time-series dataset. We conclude with a discussion of the state of the field and future research directions.

AB - Dynamic graphical models aim to describe the time-varying dependency structure of multiple time-series. In this article we review research focusing on the formulation and estimation of such models. The bulk of work in graphical structurelearning problems has focused in the stationary i.i.d setting, we present a brief overview of this work before introducing some dynamic extensions. In particular we focuson two classes of dynamic graphical model; continuous (smooth) models which are estimated via localised kernels, and piecewise models utilising regularisation based estimation. We give an overview of theoretical and empirical results regarding these models, before demonstrating their qualitative difference in the context of a real-world financial time-series dataset. We conclude with a discussion of the state of the field and future research directions.

KW - Graphical model

KW - Sparsity

KW - Changepoint

KW - Time-series

KW - Dynamics

KW - Regularization

U2 - 10.1007/978-3-319-44412-3_8

DO - 10.1007/978-3-319-44412-3_8

M3 - Conference contribution/Paper

SN - 9783319444123

SP - 111

EP - 128

BT - Advanced Analysis and Learning on Temporal Data: First ECML PKDD Workshop, AALTD 2015, Porto, Portugal, September 11, 2015, Revised Selected Papers

A2 - Douzal-Chouakria, Ahlame

A2 - Vilar, José A.

A2 - Marteau, Pierre-François

PB - Springer International Publishing AG

CY - Cham

ER -