-------- Forwarded Message --------
Subject: [AISWorld] 3rd CFP [Due: April 30th] for the special track on Causal Learning of the IEEE International Conference on Smart Data Services 2021, Virtual, 5-10 September 2021
Date: Mon, 19 Apr 2021 10:20:05 -0700
From: Ruocheng Guo <rguo12@asu.edu>
To: aisworld@lists.aisnet.org


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 (Extended Deadline)


- Normal paper submission: April 30, 2021
- Rebuttal phase: June 15 – 21, 2021
- Final notification to authors: June 30, 2021
- Camera-ready paper and registration due: July 15, 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@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@asu.edu
Arizona State University
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