Connectionists: KDD 2019 Workshop: Data Collection, Curation, and Labeling for Mining and Learning.

[Giulia D]

We are excited to announce a call for papers for the KDD 2019 Workshop:

Data Collection, Curation, and Labeling for Mining and Learning
<https://sites.google.com/corp/view/kdd-workshop-2019/home>

This workshop will provide a concentrated venue for experts in (1) data
collection, (2) data curation, and (3) data labeling to not only discuss
their latest results, but also to present their positions on the direction
of the field. One goal we strive for, in particular, is eliciting insights
on how to better align theoretical and empirical endeavors.

We solicit submission of research papers from any area of machine learning
that overlap with the data-centered tasks mentioned above. An incomplete
list of areas includes:

   -

   Active Learning
   -

   Crowdsourcing
   -

   Fairness
   -

   Semi-supervised Learning
   -

   Reinforcement Learning
   -

   Data Mining
   -

   Sequential Decision Processes

For more detailed information, please see our website
<https://sites.google.com/corp/view/kdd-workshop-2019/home>.

All submissions must adhere to KDD 2019 style format with a 4 page limit
including figures. An additional fifth page may be used to cite references.
We allow for supplementary material, although the committee is not required
to review it when making their decisions. The authors may decide whether
they would like to make a blind or non-blind submission. The papers will be
reviewed by the organizers and the program committee. All accepted papers
will present a poster and the best paper will be given an oral presentation
slot.

Important dates:

   -

   Submission deadline: May 5, 2019
   -

   Acceptance decisions:  June 1, 2019
   -

   Camera-ready version:  June 15, 2019

Please submit the papers to dataworkshopkdd at gmail.com. The organizers are
Corinna Cortes, Michael Collins, Giulia DeSalvo, Claudio Gentile, Isabelle
Guyon, Mehryar Mohri, Afshin Rostamizadeh, and Ningshan Zhang.

Best,

Giulia DeSalvo
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