Difference between revisions of "Community/training/2019"

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(Programme)
(Programme)
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We are still working to confirm instructors at the winter school
 
We are still working to confirm instructors at the winter school
 
but expect to collaborate with the organizers of the
 
but expect to collaborate with the organizers of the
[lxmls.it.pt Lisbon Machine Learning School] (LxML) and
+
[http://lxmls.it.pt Lisbon Machine Learning School] (LxML) and
 
borrow some of their experience and course materials.
 
borrow some of their experience and course materials.

Revision as of 09:17, 10 November 2017

Background

A desirable side-effect of the NLPL cooperation is community formation, i.e. strengthening interaction and collaboration among Nordic research teams in NLP and advancing a shared level of knowledge and experience in using national e-Infrastructures for large-scale NLP research. Towards these goals, the project will organize some training and outreach events.

For early 2018, NLPL will hold a winter school in conjunction with the NeIC All-Hands Meeting (AHM), to which some NLPL team members will be invited. The NeIC meeting will be held from January 29 to February 1, 2018, in the Norwegian mountain resort at Skeikampen.

Probably starting after lunch on Monday, January 29, NLPL will kick off its winter school in E-Infrastructure and Scientific Computing for Nordic Natural Language Processing Research. The winter school will have a duration of two days, i.e. end before lunch on Wednesday, January 31. We anticipate participation of around 20 people, where the majority will come from the NLPL partner sites. NLPL team members, associates at partner sites (e.g. doctoral and post-doctoral fellows, possibly also some MSc students), and other prospective users of the infrastructure will be invited to attend; NLPL partners can have their cost of participation covered by the project.

Programme

The winter school will comprise different types of activities, including (a) overview talks, for example on GPU programming (with emphasis on Taito and Abel), ‘deep’ learning paradigms and toolkits, or other scientific programming and HPC techniques; (b) in-depth tutorials on parts of the NLPL infrastructure (e.g. translation, parsing, and extrinsic evaluation software, as well as corpora and embeddings) and other topics of relevance to the project (e.g. ‘containerization’); and (c) hands-on hackathons, i.e. collective programming and experimentation in specific toolkits (e.g. environments like DyNet, MPI, or CUDA). Participation in the hackathons will require preparation prior to the winter school, which NLPL partner sites will organize locally.

We are still working to confirm instructors at the winter school but expect to collaborate with the organizers of the Lisbon Machine Learning School (LxML) and borrow some of their experience and course materials.