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
ISBN: 9781450364836
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