Dear friends in causality research.
Welcome to the 2018 Winter greeting from the UCLA Causality
Blog. causality.cs.ucla.edu/blog


This greeting discusses the following topics:

1.  A report is posted, on the "What If" workshop 
   at the NIPS conference.  (see December 19, 2017 post below)
  It discusses my presentation of: Theoretical Impediments
  to Machine Learning, a newly revised version of which can be 
viewed here.  http://ftp.cs.ucla.edu/pub/stat_ser/r475.pdf]
  
2. New posting:
"Facts and Fiction from "the Missing Data Framework".
 Inviting discussion of two familiar mantras:
Mantra-1.
"The role of missing data analysis in causal inference is
well understood (eg causal inference theory based on
counterfactuals relies on the missing data framework).
and
Mantra-2.  
"while missing data methods can form tools for causal
inference, the converse cannot be true."

We explain why we believe both mantras to be false,
but we would like to hear you opinion before firming up
our mind.

3. A review paper is available here:
  http://ftp.cs.ucla.edu/pub/stat_ser/r473.pdf
 Titled: "Graphical Models for Processing Missing Data"
  It explains and demonstrates why missing data
  is a causal inference problem.
   
4. A new page is now up, providing information on "The Book of Why"
http://bayes.cs.ucla.edu/WHY/
It contains Table of Contents and excerpts from the book.

5. Nominations are now open for the ASA Causality in Education Award.
   The nomination deadline is March 1, 2018.
For more information, please see 
http://www.amstat.org/education/causalityprize/.

6. For those of us who were waiting patiently for 
the Korean translation of Primer -- our long wait is 
finally over. The book is available now in colorful cover 
and in optimistic North Korean accent.
http://www.kyowoo.co.kr/02_sub/view.php?p_idx=1640&cate=0014_0017_ 

Dont miss the gentlest introduction to causal inference.
http://bayes.cs.ucla.edu/PRIMER/ 

Enjoy and have a productive 2018.

Judea

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