Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings - Part III

Publikation: Bücher und AnthologienSammelwerke und AnthologienForschung

Authors

  • Ulf Brefeld (Herausgeber*in)
  • Edward Curry (Herausgeber*in)
  • Elizabeth Daly (Herausgeber*in)
  • Brian MacNamee (Herausgeber*in)
  • Alice Marascu (Herausgeber*in)
  • Fabio Pinelli (Herausgeber*in)
  • Michele Berlingerio (Herausgeber*in)
  • Neil Hurley (Herausgeber*in)

The proceedings contain 12 papers. The special focus in this conference is on Mining Data for Financial Applications. The topics include: Privacy risk for individual basket patterns; exploring students eating habits through individual profiling and clustering analysis; calibrating the mean-reversion parameter in the hull-white model using neural networks; deep factor model: Explaining deep learning decisions for forecasting stock returns with layer-wise relevance propagation; a comparison of neural network methods for accurate sentiment analysis of stock market tweets; a progressive resampling algorithm for finding very sparse investment portfolios; ICIE 1.0: A novel tool for interactive contextual interaction explanations; testing for self-excitation in financial events: A bayesian approach; a web crawling environment to support financial strategies and trend correlation: – extended abstract –; a differential privacy workflow for inference of parameters in the rasch model.

OriginalspracheEnglisch
ErscheinungsortCham
VerlagSpringer
Band11053
Anzahl der Seiten706
ISBN (Print)978-3-030-10996-7
ISBN (elektronisch)978-3-030-10997-4
DOIs
PublikationsstatusErschienen - 2019
VeranstaltungEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECML PKDD 2018 - Dublin, Irland
Dauer: 10.09.201814.09.2018
http://www.ecmlpkdd2018.org/

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band11054 LNAI
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349

DOI

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