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<p>Dear all,</p>
<div>We would like to notify you that we extended the submission
deadline for the AutoML workshop at ICML'20 by roughly a month
because because as ICML being a virtual event, we do not need to
budget time for visa applications.</div>
<div><br>
</div>
<div><b>The new submission deadline will be May 20th and the author
notification on June 17th.</b></div>
<div><br>
</div>
<div>For more details, please see the email below and the workshop
website <a href="http://icml2020.automl.org/">icml2020.automl.org</a></div>
<div><br>
</div>
On behalf of the organizing committee,<br>
<p>Matthias Feurer<br>
</p>
<p><br>
</p>
<div class="moz-cite-prefix">On 28.03.20 18:06, Frank Hutter wrote:<br>
</div>
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<div>Dear all, <br>
</div>
<div><br>
</div>
<div>We're happy to announce the 7th ICML Workshop on Automated
Machine Learning (AutoML), which will be held on July 17 or
July 18, 2020, as part of the ICML conference (as a virtual
event, like ICML).</div>
<br>
<span style="font-size:11pt;color:rgb(0,0,0);background-color:transparent;font-weight:400;font-style:normal;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre-wrap"></span>Machine
learning has achieved considerable successes in recent years,
but this success often relies on human experts, who construct
appropriate features, design learning architectures, set their
hyperparameters, and develop new learning algorithms. Driven by
the demand for off-the-shelf machine learning methods from an
ever-growing community, the research area of AutoML targets the
progressive automation of machine learning aiming to make
effective methods available to everyone. Hence, the workshop
targets a broad audience ranging from core machine learning
researchers in different fields of ML connected to AutoML, such
as neural architecture search, hyperparameter optimization,
meta-learning, and learning to learn, to domain experts aiming
to apply machine learning to new types of problems.<br>
<br>
<p><b>We invite submissions on the topics of:</b><br>
</p>
<ul>
<li> Model selection, hyper-parameter optimization, and
model search</li>
<li> Neural architecture search</li>
<li> Meta-learning and transfer learning</li>
<li> Bayesian optimization for AutoML</li>
<li> Evolutionary algorithms for AutoML</li>
<li> Multi-fidelity optimization</li>
<li> Predictive models of performance</li>
<li> Automatic feature extraction / construction</li>
<li> Automatic data cleaning</li>
<li> Automatic generation of workflows / workflow reuse</li>
<li> Automatic problem "ingestion" (from raw data and
miscellaneous formats)</li>
<li> Automatic feature transformation to match algorithm
requirements</li>
<li> Automatic acquisition of new data (active learning,
experimental design)</li>
<li> Automatic report generation (providing insight on
automatic data analysis)</li>
<li> Automatic selection of evaluation metrics / validation
procedures</li>
<li> Automatic selection of algorithms under
time/space/power constraints</li>
<li> Automatic construction of fair and unbiased machine
learning models</li>
<li> Automation of semi-supervised and unsupervised machine
learning</li>
<li> Demos of existing AutoML systems</li>
<li> Robustness of AutoML systems (w.r.t. Randomized
algorithms, data, hardware etc.)</li>
<li> Human-in-the-loop approaches for AutoML</li>
<li> Learning to learn new algorithms and strategies</li>
<li> Hyperparameter agnostic algorithms</li>
</ul>
<b>Submission Format</b><br>
<p>We welcome submissions of up to 6 pages in JMLR Workshop and
Proceedings format (plus 10 pages for references and
appendix). All accepted papers will be presented as posters.
We will invite the 2-3 best papers for an oral plenary
presentation. We will provide PDFs of accepted papers on <a
href="http://icml2020.automl.org/" target="_blank"
moz-do-not-send="true">http://icml2020.automl.org/</a>, but
there will be no archival proceedings. For submission details
please see the submission page. <br>
</p>
<b>Remark on COVID-19</b><br>
<p>Due to the Covid-19 pandemic, ICML will be an entirely
virtual conference this year (<a
href="https://icml.cc/Conferences/2020/VirtualICML"
moz-do-not-send="true">https://icml.cc/Conferences/2020/VirtualICML</a>),
and the AutoML workshop will follow suit. We are in contact
with the ICML organizers about how this will pan out exactly
and will inform you as soon as possible. We provide up-to-date
information on <a href="http://icml2020.automl.org"
target="_blank" moz-do-not-send="true">http://icml2020.automl.org</a><br>
</p>
<p><span><span></span></span></p>
<b>Keynote Speakers</b><br>
<ul>
<li> Alex Smola (Director, Amazon Web Services)</li>
<li> Mihaela van der Schaar (Professor of Machine Learning,
Artificial Intelligence and Medicine at the University of
Cambridge) </li>
<li> Neil Lawrence (DeepMind Professor of Machine Learning
at the University of Cambridge and visiting Professor at the
University of Sheffield) </li>
</ul>
<p><b>
</b></p>
<b>Organization</b><br>
<div>
Katharina Eggensperger, Matthias Feurer, Frank Hutter, Marius
Lindauer, and Joaquin Vanschoren and Charles Weill
</div>
<p><b>Location</b><br>
</p>
<p>The 7th ICML workshop on AutoML will be co-located with the
37th International Conference on Machine Learning (ICML 2020)
and will take place on July 17th or 18th.<b><br>
</b></p>
<p><b>Important Dates</b></p>
Deadline: April 23rd (Anywhere on earth) <br>
Notification: May 25th (Anywhere on earth) <br>
<p><span><span>On behalf of the organizing committee,</span></span><br>
Frank Hutter</p>
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