CFP : Workshop@IEEE ICDM '20 Large-scale Industrial Time Series Analysis
Mustapha Lebbah
Dear all,
We are pleased to announce the Call for Papers for the 1st edition of the workshop “Large-scale Industrial Time Series Analysis” (LITSA), hosted by the IEEE ICDM 2020 conference in Sorrento, Italy.
Workshop on Large-scale Industrial Time Series Analysis In conjunction with: 20th IEEE International Conference on Data Mining (ICDM 2020)
https://lipn.github.io/LITSA2020/
IMPORTANT DATES
- August 24, 2020: Workshop papers submission
- September 17, 2020: Notification of workshop papers
acceptance to authors
- September 24, 2020: Camera-ready deadline and copyright
form
- November 17, 2020: Workshops date
Papers must be formatted and written according to the Submission
Guidelines on the ICDM 2020 conference web site. You are strongly
encouraged to print and double check your PDF file before its
submission, especially if your paper contains Asian/European
language symbols (such as Chinese/Korean characters or English
letters with European fonts).
SCOPE
One of the greatest challenges currently faced by experts,
researchers and data scientists is to efficiently explore
potentially large amounts of time series. Special care has been
taken to analyze temporal data in the last century, especially in
the industrial domain: an attention that skyrocketed along the
ability to produce, collect and treat those data. Nevertheless,
time series analysis remains an open research subject, due to the
complexity of this data type and to the great amount of
information it contains. Developing general methods for
large-scale time series algorithms and data preprocessing is a
pressing demand from companies wishing to explore big data.
This workshop offers a meeting opportunity for academic and
industry researchers in the fields of machine learning, deep
learning, data visualization, data mining, data engineering and
Big Data to discuss new areas of learning methods dedicated to
time series in industrial environments. We encourage researchers
and practitioners to submit papers describing original research
addressing time series and scalable machine learning challenges.
This includes but is not restricted to the following topics:
- Clustering and unsupervised learning
- Time Series Classification
- (Multivariate) Time Series Representations
- Deep learning approaches
- Online learning algorithms
- Mixture models and model-based methods
- Methods of detecting changes in evolving data (streaming and time series)
- Visualization
- Theoretical frameworks for time series mining
- Scalable algorithms for big data
- Parallel and distributed computing for time series analytics (cloud, map-reduce, etc.)
- Interactive mining techniques
- Collaborative methods
- Future research challenges of time series analysis
Florent Forest (Safran Aircraft Engines)
Etienne Goffinet (Groupe Renault)
Hanane Azzag (Sorbonne Paris Nord University)
Mustapha Lebbah (Sorbonne Paris Nord University)
We look forward to exchanging around these topics at ICDM and
reading your submissions,
Regards,
LITSA Workshop Organizing Team,
Université Sorbonne Paris Nord,
Laboratoire d'Informatique de Paris-Nord (LIPN),
CNRS(UMR 7030),
99, av. J-B Clément
F-93430, Villetaneuse, France.
Tel: +331 49 40 38 94
Fax: +331 48 26 07 12
http://www-lipn.univ-paris13.fr/~lebbah