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CALL FOR PAPERS:

-----------------------------

We invite participation in NIPS 2017 Workshop:

“From 'What If?' To 'What Next?' : Causal Inference and Machine Learning
for Intelligent Decision Making” -- December 8th  2017,  Long Beach, USA.

Website: sites.google.com/view/causalnips2017


IMPORTANT DATES:

-----------------------------

   -

   Submission deadline for abstracts and papers: October 31, 2017
   -

   Acceptance decisions: November 7, 2017



INVITED TALKS:
-----------------------

Leon Bottou (Facebook, US)

Emma Brunskill (CMU)
Guido Imbens (Stanford)

Jasjeet Sekhon (UC Berkeley)

David Sontag (MIT)
Matt Taddy (Microsoft)


Overview

In recent years machine learning and causal inference have both seen
important advances, especially through a dramatic expansion of their
theoretical and practical domains. This workshop is aimed at facilitating
more interactions between researchers in machine learning, causal
inference, and application domains that use both for intelligent decision
making. To this effect, the 2017 'What If?' To 'What Next?' workshop
welcomes contributions from a variety of perspectives from machine
learning, statistics, economics and social sciences, among others. This
includes, but it is not limited to, the following topics:

-          Combining experimental control and observational data

-          Bandit algorithms and reinforcement learning with explicit links
to causal inference and counterfactual reasoning

-          Interfaces of agent-based systems and causal inference

-          Handling selection bias

-          Large-scale algorithms

-          Applications in online systems (e.g. search, recommendation, ad
placement)

-          Applications in complex systems (e.g. cell biology, smart
cities, computational social sciences)

-          Interactive experimental control vs. counterfactual estimation
from logged experiments

-          Discriminative learning vs. generative modeling in
counterfactual settings

We invite contributions both in the form of extended abstract and full
papers. At the discretion of the organizers, some contributions will be
assigned slots as short contributed talks and others will be presented as
posters.

Submission Instructions:
-----------------------------------

Submission website https://cmt3.research.microsoft.com/WhatIF2017/

Submission length: 2 page extended abstracts or up to 8 page full paper
Please use the NIPS 2017 submission format

Please note that at least one author of each accepted paper must be
available to present the paper at the workshop.


Organizing Committee:
---------------------------------

Thorsten Joachims <http://www.cs.cornell.edu/People/tj/>, Information
Science and Computer Science, Cornell University

Nathan Kallus <http://www.nathankallus.com/>, Cornell Tech and ORIE,
Cornell University

Lihong Li <https://www.microsoft.com/en-us/research/people/lihongli/>, Deep
Learning Technology Center, Microsoft Research

Adith Swaminathan
<https://www.microsoft.com/en-us/research/people/adswamin/>, Deep Learning
Technology Center, Microsoft Research

Ricardo Silva <http://www.homepages.ucl.ac.uk/~ucgtrbd/>, Statistical
Science, UCL

John S Shawe-Taylor <http://www0.cs.ucl.ac.uk/staff/J.Shawe-Taylor/>,
Computer Science, UCL

Panos Toulis <http://faculty.chicagobooth.edu/Panagiotis.Toulis/index.html>,
Econometrics and Statistics, Booth School of Business, University of Chicago
Alexander Volfovsky <https://volfovsky.github.io/>, Statistical Science,
Duke University

-- 
best
panos

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