The summer school takes place at the university's Seminar Building, Friedrich-Wöhler-Weg 6.
Machine learning is the key technology to discover information and concepts hidden in huge amounts of data. At the same time, availability of data is ever increasing. Better sensors deliver more accurate and fine-grained data, more sensors a more complete view of the scenario. While this should lead to better learning results, it comes at a cost: Resources for the learning task are limited, restricted by computational power, communication restrictions or energy constraints. The increased complexity needs a new class of algorithms respecting the constraints.
From to , the TU Dortmund University, Germany, will host a summer school addressing solutions to these constraints.
For the summer school, world leading researchers in machine learning and embedded systems are giving lectures on several techniques dealing with huge amounts of data, distributed data and constraints of embedded systems.
The summer school is open for international PhD or advanced master students, who want to learn cutting edge techniques for machine learning with constrained resources. Available slots for participants are strictly limited, so it is essential to register early. Excellent students may apply for a student grant to fund travel and accommodation.
The international summer school on resource-aware maching learning is part of the graduate school of the Collaborative Research Center SFB 876. The research center targets both ends of the machine learning spectrum: Small devices, with high restrictions due to the device, and high-dimensional data with a complexity exceeding even large computing center's capacity.
Registration Summer School 2017
Register here as a participant for the summer school. Rates are 350,-€ for early and 400,-€ for late registrations, see Important Dates. The registration includes access to all lectures, the lecture materials, the summer school Wiki, the welcome breakfast, coffee breaks and the banquet dinner.
Shortly after registration for the summer school you will receive an invoice for the registration fee via email. The fee has to be sent via bank transfer and you will only be allowed to attend the summer school after we received your payment. On-site registration is not possible.
Important Dates Summer School 2017
|Registration Opens||1st of March 2017|
|Early Registration Deadline||30th of June 2017
Early registration fee is 350,-€.
|Late Registration Deadline||31st of August 2017
Late registration fee is 400,-€. No on-site registration or payment is possible.
|Application Deadline for Student Grants||15th of July 2017|
|Student Grant Decision||25th of July 2017|
|Summer School||25th - 28th of September 2017|
Student Grants Summer School 2017
Student grants covering travel and accommodation up to 500,-€ will be sponsored. A committee will select up to five of the best students. The criteria are the quality of the student and the distribution of student grants over the world. Applications are to be addressed to Prof Dr. Katharina Morik via email to firstname.lastname@example.org and must include the following:
- Applicant's CV.
- Information about existing knowledge in machine learning or embedded systems, e.g. a list of previous lectures or courses and the grades you received.
- Recommendation of the supervisor and/or a lecturer of the Summer School.
- In case you published conference papers etc. on topics related to the summer school, please attach one publication you consider most valuable.
- We expect you to give a short talk (10 min) about your work (e.g. thesis or research papers) during the summer school. Please include a proposal for your talk (preliminary title and short abstract) in your application. The topic of the talk does not necessarily have to be related to the topics of the summer school.
Application for student grants is open from 1st of March to 15th of July. The decision on grants will be made on 25th of July.
For more information please click "Further Official Information" below.
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