Unsupervised Transfer Learning for Time Series via Self-Predictive Modelling - First Results

Aswolinskiy W, Hammer B (2017)
In: Proceedings of the Workshop on New Challenges in Neural Computation (NC2). Machine Learning Reports, 03/2017. Bielefeld: Universität Bielefeld, CITEC.

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Conference Paper | Published | English
Abstract
Real-world machine learning applications must be able to adapt to systematic changes in the data, e.g. a new subject or sensor displacement. This can be seen as a form of transfer learning, where the goal is to reuse the old (source) model by adapting the new (target) data. This is a challenging task, if no labels for the target data are available. Here, we propose to use the structure of the source and target data to find a transformation from the source to target space in an unsupervised manner. Our preliminary experiments on multivariate time series data show the feasibility of the approach, but also its limits.
Publishing Year
Conference
Workshop on New Challenges in Neural Computation (NC2)
Location
Basel
Conference Date
2017-09-12
ISSN
PUB-ID

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Aswolinskiy W, Hammer B. Unsupervised Transfer Learning for Time Series via Self-Predictive Modelling - First Results. In: Proceedings of the Workshop on New Challenges in Neural Computation (NC2). Machine Learning Reports. Vol 03/2017. Bielefeld: Universität Bielefeld, CITEC; 2017.
Aswolinskiy, W., & Hammer, B. (2017). Unsupervised Transfer Learning for Time Series via Self-Predictive Modelling - First Results. Proceedings of the Workshop on New Challenges in Neural Computation (NC2), Machine Learning Reports, 03/2017 Bielefeld: Universität Bielefeld, CITEC.
Aswolinskiy, W., and Hammer, B. (2017). “Unsupervised Transfer Learning for Time Series via Self-Predictive Modelling - First Results” in Proceedings of the Workshop on New Challenges in Neural Computation (NC2) Machine Learning Reports, vol. 03/2017, (Bielefeld: Universität Bielefeld, CITEC).
Aswolinskiy, W., & Hammer, B., 2017. Unsupervised Transfer Learning for Time Series via Self-Predictive Modelling - First Results. In Proceedings of the Workshop on New Challenges in Neural Computation (NC2). Machine Learning Reports. no.03/2017 Bielefeld: Universität Bielefeld, CITEC.
W. Aswolinskiy and B. Hammer, “Unsupervised Transfer Learning for Time Series via Self-Predictive Modelling - First Results”, Proceedings of the Workshop on New Challenges in Neural Computation (NC2), Machine Learning Reports, vol. 03/2017, Bielefeld: Universität Bielefeld, CITEC, 2017.
Aswolinskiy, W., Hammer, B.: Unsupervised Transfer Learning for Time Series via Self-Predictive Modelling - First Results. Proceedings of the Workshop on New Challenges in Neural Computation (NC2). Machine Learning Reports. 03/2017, Universität Bielefeld, CITEC, Bielefeld (2017).
Aswolinskiy, Witali, and Hammer, Barbara. “Unsupervised Transfer Learning for Time Series via Self-Predictive Modelling - First Results”. Proceedings of the Workshop on New Challenges in Neural Computation (NC2). Bielefeld: Universität Bielefeld, CITEC, 2017.Vol. 03/2017. Machine Learning Reports.
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