[AISWorld] Call for papers for the special track on Causal Learning of the IEEE International Conference on Smart Data Services 2021, Virtual, 5-10 September 2021: submit until 15 April 2021

[Ruocheng Guo]

Special Track on Causal Learning
of the IEEE International Conference on Smart Data Services (SMDS'21)
5-10 September 2021
Online Virtual Conference
https://conferences.computer.org/smds/2021/

<https://conferences.computer.org/smds/2021/>
Topics covered:

   - Causal learning from observational big data
   - Causal learning with streaming data
   - Causality and explainability
   - Causally informed data analytics
   - Benchmarking for causal learning
   - Applications of causal learning in smart data services


Important dates


   - Optional early paper submission: March 1, 2021
   - Improvement suggestions to early papers: April 1, 2021
   - Normal paper submission: April 15, 2021
   - Rebuttal phase: June 1 - 7, 2021
   - Final notification to authors: June 17, 2021
   - Camera-ready paper and registration due: July 1, 2021


All submission deadlines are AT 5:00AM UTC.

Author guidelines (full version at
https://conferences.computer.org/smds/2021/cfp/)

   - Every* full paper submission *can include up to *10 pages* for the
   main contents (including all text, footnotes, figures, tables and
   appendices) with additional pages for appropriate references.
   - Up to* three pages* for *“Work-in-Progress” paper* submission
   (including main contents and references).
   - Please note that the above page limit will be applied without
   exception. Papers violating the page limit will regretfully be desk
   rejected.


Full more details of the submission process are on the Call for Papers page
on the conference website.

Please submit your SMDS paper at EasyChair.org:
https://easychair.org/conferences/?conf=ieeesmds2021

Please read the FAQ
<https://conferences.computer.org/services/2021/overview/faq.html> before
emailing CFP inquiries to:
ieeecs.smds at gmail.com.

Special Track on Causal Learning Chairs
Huan Liu                              Arizona State University, Tempe, AZ,
USA
Ruocheng Guo                    Arizona State University, Tempe, AZ, USA

Best regards,

-- 
*Ruocheng Guo*

Ph.D. student in Computer Engineering
Data Mining and Machine Learning Lab

*Homepage:* www.public.asu.edu/~rguo12
*Email:* rguo12 at asu.edu
Arizona State University