<div dir="ltr"><div style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0)" class="elementToProof gmail-ContentPasted0 gmail-ContentPasted2"><span style="font-size:16pt"><b>First Edinburgh Workshop on Affordable Machine Learning</b></span><br></div><div style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0)" class="elementToProof gmail-ContentPasted0 gmail-ContentPasted2"><br></div><div style="font-family:Calibri,Arial,Helvetica,sans-serif;font-size:12pt;color:rgb(0,0,0)" class="elementToProof gmail-ContentPasted0 gmail-ContentPasted2">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: <a href="https://www.eventbrite.co.uk/e/the-first-edinburgh-workshop-on-affordable-machine-learning-tickets-638066683627" id="gmail-LPNoLPOWALinkPreview">https://www.eventbrite.co.uk/e/the-first-edinburgh-workshop-on-affordable-machine-learning-tickets-638066683627</a><div class="gmail-_Entity gmail-_EType_OWALinkPreview gmail-_EId_OWALinkPreview gmail-_EReadonly_1"></div><div><br class="gmail-ContentPasted0"></div><div class="gmail-ContentPasted0">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.</div><div><br class="gmail-ContentPasted0"></div><div class="gmail-ContentPasted0">We
 invite submissions of (published or unpublished) work that is relevant 
to the topic of the workshop. This includes, but is not limited to:</div><div class="gmail-ContentPasted0"><ul><li style="list-style-type:disc">Issues with efficiently implementing machine learning algorithms</li><li class="gmail-ContentPasted0" style="list-style-type:disc">Methods for data-efficient learning: few-shot learning, meta-learning, continual learning, transfer learning, etc</li><li class="gmail-ContentPasted0" style="list-style-type:disc">Active learning and coreset selection</li><li class="gmail-ContentPasted0" style="list-style-type:disc">Optimisation for machine learning</li><li class="gmail-ContentPasted0" style="list-style-type:disc">Efficient hyperparameter optimisation techniques</li><li class="gmail-ContentPasted0" style="list-style-type:disc">Tractable Probabilistic Modelling</li><li class="gmail-ContentPasted0" style="list-style-type:disc">Applications in vision, language, biomedicine, robotics, etc where compute or data efficiency are required</li></ul></div><div class="gmail-ContentPasted0 gmail-ContentPasted3">Submissions will be screened for relevance, but not peer reviewed. Please submit you work using this short form: <a href="https://forms.office.com/e/Yes62a9H6y" id="gmail-LPlnk467746">https://forms.office.com/e/Yes62a9H6y</a></div><div><br class="gmail-ContentPasted0"></div><div class="gmail-ContentPasted0">The workshop will feature invited talks from academics and industry leaders:</div><div class="gmail-ContentPasted0"><ul><li style="list-style-type:disc">Andrew Fitzgibbon (Graphcore)</li><li class="gmail-ContentPasted0" style="list-style-type:disc">Megan J. Stanley (Microsoft Research)</li><li class="gmail-ContentPasted0" style="list-style-type:disc">Jan N. van Rijn (Leiden University)</li><li class="gmail-ContentPasted0" style="list-style-type:disc">Tengda Han (University of Oxford)</li><li class="gmail-ContentPasted0" style="list-style-type:disc">Sarah Parisot (Huawei Noah's Ark Lab)</li></ul></div><div class="gmail-ContentPasted0 gmail-ContentPasted1">More information about the programme is available on our website: <a href="https://www.bayeswatch.com/affordable_ml/" id="gmail-LPlnk692874">https://www.bayeswatch.com/affordable_ml/</a></div><div><br class="gmail-ContentPasted0"></div><div class="gmail-ContentPasted0">We look forward to seeing you!</div><div><br class="gmail-ContentPasted0"></div><div><br class="gmail-ContentPasted0"></div><div class="gmail-ContentPasted0">Best,</div><div><br class="gmail-ContentPasted0"></div><div class="gmail-ContentPasted0">Henry Gouk, Elliot J. Crowley, Amos Storkey</div>Workshop organisers</div></div>