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Scalable online learning for flink: SOLMA library

Authors: Jamil, W., Duong, N.C., Wang, W., Mansouri, C., Mohamad, S. and Bouchachia, A.

Journal: ACM International Conference Proceeding Series

DOI: 10.1145/3241403.3241438

Abstract:

Driven by the needs of Flink to expand the offline engine to a hybrid one, a new machine learning (ML) library, called SOLMA is proposed. This library aims to cover online learning algorithms for data streams. In this setting, data streams are processed sequentially example by example. SOLMA, which is under development, currently contains two classes of algorithms: (i) basic streaming routines such as online sampling, online PCA, online statistical moments and (ii) advanced online ML algorithms covering in particular classification, regression and drift/anomaly detection and handling. This paper briefly highlights the concepts underlying SOLMA.

https://eprints.bournemouth.ac.uk/31449/

Source: Scopus

Scalable Online Learning for Flink SOLMA Library

Authors: Jamil, W., Duong, N.-C., Wang, W., Mansouri, C., Mohamad, S. and Bouchachia, A.

Journal: ECSA 2018: PROCEEDINGS OF THE 12TH EUROPEAN CONFERENCE ON SOFTWARE ARCHITECTURE: COMPANION PROCEEDINGS

DOI: 10.1145/3241403.3241438

https://eprints.bournemouth.ac.uk/31449/

Source: Web of Science (Lite)

Scalable online learning for flink: SOLMA library

Authors: Jamil, W., Duong, N.C., Wang, W., Mansouri, C., Mohamad, S. and Bouchachia, A.

Conference: ECSA '18: 12th European Conference on Software Architecture

Publisher: ECSA '18 Proceedings of the 12th European Conference on Software Architecture: Companion Proceedings Article No. 33

ISBN: 9781450364836

Abstract:

Driven by the needs of Flink to expand the offline engine to a hybrid one, a new machine learning (ML) library, called SOLMA is proposed. This library aims to cover online learning algorithms for data streams. In this setting, data streams are processed sequentially example by example. SOLMA, which is under development, currently contains two classes of algorithms: (i) basic streaming routines such as online sampling, online PCA, online statistical moments and (ii) advanced online ML algorithms covering in particular classification, regression and drift/anomaly detection and handling. This paper briefly highlights the concepts underlying SOLMA.

https://eprints.bournemouth.ac.uk/31449/

Source: BURO EPrints