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About

The age of "big data" is here: data of unprecedented sizes is becoming ubiquitous, which brings new challenges and new opportunities. With this comes the need to solve optimization problems of unprecedented sizes. Machine learning, compressed sensing, social network science and computational biology are some of many prominent application domains where it is increasingly common to formulate and solve optimization problems with billions of variables. Classical algorithms are not designed to scale to instances of this size and hence new approaches are needed. These approaches utilize novel algorithmic design involving tools such as distributed and parallel computing, randomization, asynchronicity, decomposition, sketching and streaming. This workshop aims to bring together researchers working on novel optimization algorithms and distributed systems capable of working in the Big Data setting.

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History

This will be the fourth edition of this workshop series. Previous editions were organized at the University of Edinburgh in 20152013, and 2012.

Audience

Anyone interested in the newest developments in big data optimization algorithms, theory, applications, and systems.

Contributed posters and spotlight talks

The workshop invites the submission of contributed abstracts (up to 1,000 characters, sent as pure text via email). All accepted abstracts will be presented in the form of posters and selected abstracts will, in addition, be given the space of 5 minutes for a spotlight oral talk.

There will be a poster session at the workshop, providing an opportunity to international and KAUST MS and PhD students to present their research, and an excellent venue for extended informal discussion with conference attendees. The poster session will be preceded by a session of short talks (a few minutes) advertising the posters.

There will be Best Contribution Award and Best In-Kingdom Contribution Award for the best spotlight talk and poster combination from the overall contributions and the set of in-kingdom contributions, respectively. The award is sponsored by the KAUST Industry Collaboration Program (KICP), Industry Partnerships office.

Dates

  • January 15, 2018: Submission deadline for abstracts. Submit to peter.richtarik@kaust.edu.sa.

  • January 18, 2018: Notification of selected posters.

  • January 20, 2018: Registration deadline.
  • January 24, 2018: Final submission of the accepted posters. Send the file in PDF format to peter.richtarik@kaust.edu.sa. If you'd like us to print your poster, indicate it in your email. 

Sponsors

With financial support from the KAUST Office of Sponsored Research. Co-sponsored by the Alan Turing Institute (United Kingdom), and additional support provided by the KAUST Industry Collaboration Program (KICP), Industry Partnerships office.