Connectionists: Eastern European Machine Learning summer school (EEML), Hybrid in Vilnius, Lithuania, 6-14 July 2022, DEADLINE FOR APPLICATIONS April 7, 2022

[Razvan Pascanu]

Call for Participation (apologies for crossposting)

Eastern European Machine Learning summer school (**with online and
in-person sections**)

July 6-14, 2021, Vilnius, Lithuania

Web: https://www.eeml.eu

Email: contact at eeml.eu

Applications are open! Details about the application process
https://www.eeml.eu/application.

Application closes: April 7, 2022

Notification of acceptance: Early May 2022.

**Registration will be free for all accepted participants, for both online
and in-person attendance.**

Motivation and description

EEML is a machine learning summer school that aims to democratise access to
education and research in AI, and improve diversity in the field. The
summer school is held yearly in Eastern Europe – this year it will be held
in Vilnius, Lithuania. Because of the pandemic, the school will use a
hybrid format: first 3 days fully online, last 4 days online and in-person
for those who wish to travel to Vilnius; check details on our webpage
https://www.eeml.eu/program.

By bringing together (virtually or in-person) high quality lecturers and
participants from all over the world, we strive to enable communication and
networking among the Eastern European AI communities as well as with
researchers from around the world.

The school is open to participants from all over the world. The selection
process has equal opportunities and diversity at heart, and will assess
interest and knowledge in machine learning. We encourage applications from
candidates at all levels of expertise in Machine Learning (beginner,
intermediate, advanced). Details about the application process are
available online at https://www.eeml.eu/application.

The programme consists of lectures, reading groups, hands-on practical
sessions, panel discussions, and more. Some of the core topics to be
covered include Reinforcement Learning, Natural Language Processing,
Computer Vision, Theory of Deep Learning, Causal Inference.

List of confirmed speakers (so far)

Doina Precup, McGill University & DeepMind

Ferenc Huszar, University of Cambridge

Finale Doshi-Velez, Harvard University

Gintare Karolina Dziugaite, Google Research

Michal Valko, DeepMind

Razvan Pascanu, DeepMind

Suriya Gunasekar, Microsoft Research Redmond

Victor Lempitsky, Skoltech & Samsung

Yee Whye Teh, University of Oxford & DeepMind


Poster session

Participants will have the opportunity to present their research work and
interests during virtual poster sessions. The work described does not have
to be novel. For example, participants can present their experience of
reproducing published work.


Organizers

Doina Precup, McGill University & DeepMind

Razvan Pascanu, DeepMind

Viorica Patraucean, DeepMind

Ferenc Huszar, University of Cambridge

Gintare Karolina Dziugaite, Google Research

Jevgenij Gamper, Vinted

Linas Petkevičius, Vilnius University

Dovydas Čeilutka, Vinted

Linas Baltrūnas, Wayfair



Technical support



Gabriel Marchidan, IasiAI & Feel IT Services

ZoomTV


Partners

Artificial Intelligence Association of Lithuania

Faculty of Mathematics and Informatics, Vilnius University


Local Sponsors

Go Vilnius


More info

https://www.eeml.eu

contact at eeml.eu

Follow us on Twitter https://twitter.com/EEMLcommunity
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