Muutke küpsiste eelistusi

E-raamat: Advanced Analytics and Learning on Temporal Data: 9th ECML PKDD Workshop, AALTD 2024, Vilnius, Lithuania, September 9-13, 2024, Revised Selected Papers

Edited by , Edited by , Edited by , Edited by , Edited by , Edited by , Edited by
Teised raamatud teemal:
  • Formaat - PDF+DRM
  • Hind: 123,49 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

This book constitutes the refereed proceedings of the 9th ECML PKDD workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2024, held in Vilnius, Lithuania, during September 9-13, 2024.





The 8 full papers presented here were carefully reviewed and selected from 15 submissions. The papers focus on recent advances in Temporal Data Analysis, Metric Learning, Representation Learning, Unsupervised Feature Extraction, Clustering, and Classification.

Conformal Prediction Techniques for Electricity Price Forecasting.- Multivariate Human Activity Segmentation Systematic Benchmark with ClaSP.- Comparing the Performance of Recurrent Neural Network and Some Well Known Statistical Methods in the Case of Missing Multivariate Time Series Data.- Accurate and Efficient Real World Fall Detection Using Time Series Techniques.- Highly Scalable Time Series Classification for Very Large Datasets.- Classification of Raw MEG/EEG Data with Detach-Rocket Ensemble An Improved ROCKET Algorithm for Multivariate Time Series Analysis.- Change Detection in Multivariate data streams Online Analysis with Kernel QuantTree.- Weighted Average of Human Motion Sequences for Improving Rehabilitation Assessment.