Connectionists: Final call for contributions: Edinburgh Workshop on Affordable Machine Learning

[Henry Gouk]

*First Edinburgh Workshop on Affordable Machine Learning*

We invite you to join us for the first Edinburgh Workshop on Affordable
Machine Learning. This will take place on 30th June (09:00-17:00) at
University of Edinburgh's Informatics forum. Attendance is free, but
registration is required:
https://www.eventbrite.co.uk/e/the-first-edinburgh-workshop-on-affordable-machine-learning-tickets-638066683627

Machine learning algorithms have achieved outstanding successes in e.g.,
computer vision and natural language processing. However, the widespread
adoption of machine learning techniques often faces barriers due to high
computing and data requirements, limiting access to these powerful tools.
This workshop will provide a platform for researchers and industrial
practitioners to share insights, experiences, and innovations in developing
machine learning solutions that are both computationally affordable and
data efficient through a mixture of presentations, discussions, and
interactive sessions.

We invite submissions of (published or unpublished) work that is relevant
to the topic of the workshop. This includes, but is not limited to:

   - Issues with efficiently implementing machine learning algorithms
   - Methods for data-efficient learning: few-shot learning, meta-learning,
   continual learning, transfer learning, etc
   - Active learning and coreset selection
   - Optimisation for machine learning
   - Efficient hyperparameter optimisation techniques
   - Tractable Probabilistic Modelling
   - Applications in vision, language, biomedicine, robotics, etc where
   compute or data efficiency are required

Submissions will be screened for relevance, but not peer reviewed. Please
submit you work using this short form: https://forms.office.com/e/Yes62a9H6y

The workshop will feature invited talks from academics and industry leaders:

   - Andrew Fitzgibbon (Graphcore)
   - Megan J. Stanley (Microsoft Research)
   - Jan N. van Rijn (Leiden University)
   - Tengda Han (University of Oxford)
   - Sarah Parisot (Huawei Noah's Ark Lab)

More information about the programme is available on our website:
https://www.bayeswatch.com/affordable_ml/

We look forward to seeing you!


Best,

Henry Gouk, Elliot J. Crowley, Amos Storkey
Workshop organisers
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