Learning Relevant Time Points for Time-Series Data in the Life Sciences

Schleif F-M, Mokbel B, Gisbrecht A, Theunissen L, Dürr V, Hammer B (2012)
In: ICANN (2). Lecture Notes in Computer Science, 7553. 531-539.

Download
Es wurde kein Volltext hochgeladen. Nur Publikationsnachweis!
Konferenzbeitrag | Veröffentlicht | Englisch
Abstract / Bemerkung
In the life sciences, short time series with high dimensional entries are becoming more and more popular such as spectrometric data or gene expression profiles taken over time. Data characteristics rule out classical time series analysis due to the few time points, and they prevent a simple vectorial treatment due to the high dimensionality. In this contribution, we successfully use the generative topographic mapping through time (GTM-TT) which is based on hidden Markov models enhanced with a topographic mapping to model such data. We propose an extension of GTM-TT by relevance learning which automatically adapts the model such that the most relevant input variables and time points are emphasized by means of an automatic relevance weighting scheme. We demonstrate the technique in two applications from the life sciences.
Erscheinungsjahr
Titel des Konferenzbandes
ICANN (2)
Band
7553
Seite
531-539
PUB-ID

Zitieren

Schleif F-M, Mokbel B, Gisbrecht A, Theunissen L, Dürr V, Hammer B. Learning Relevant Time Points for Time-Series Data in the Life Sciences. In: ICANN (2). Lecture Notes in Computer Science. Vol 7553. 2012: 531-539.
Schleif, F. - M., Mokbel, B., Gisbrecht, A., Theunissen, L., Dürr, V., & Hammer, B. (2012). Learning Relevant Time Points for Time-Series Data in the Life Sciences. ICANN (2), 7553, 531-539. doi:10.1007/978-3-642-33266-1_66
Schleif, F. - M., Mokbel, B., Gisbrecht, A., Theunissen, L., Dürr, V., and Hammer, B. (2012). “Learning Relevant Time Points for Time-Series Data in the Life Sciences” in ICANN (2) Lecture Notes in Computer Science, vol. 7553, 531-539.
Schleif, F.-M., et al., 2012. Learning Relevant Time Points for Time-Series Data in the Life Sciences. In ICANN (2). Lecture Notes in Computer Science. no.7553 pp. 531-539.
F.-M. Schleif, et al., “Learning Relevant Time Points for Time-Series Data in the Life Sciences”, ICANN (2), Lecture Notes in Computer Science, vol. 7553, 2012, pp.531-539.
Schleif, F.-M., Mokbel, B., Gisbrecht, A., Theunissen, L., Dürr, V., Hammer, B.: Learning Relevant Time Points for Time-Series Data in the Life Sciences. ICANN (2). Lecture Notes in Computer Science. 7553, p. 531-539. (2012).
Schleif, Frank-Michael, Mokbel, Bassam, Gisbrecht, Andrej, Theunissen, Leslie, Dürr, Volker, and Hammer, Barbara. “Learning Relevant Time Points for Time-Series Data in the Life Sciences”. ICANN (2). 2012.Vol. 7553. Lecture Notes in Computer Science. 531-539.

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Suchen in

Google Scholar
ISBN Suche