Tensor Theory and Applications Meeting


Sanderson Building, King's Buildings, EH9 3JL


Thursday, March 30, 2017 -
09:30 to 17:30

The goal of the meeting is to bring together researchers in the theory and application of tensor based methods. The scope is to disseminate the current methodology in tensor analysis and the communication of algorithms, technologies, practical issues and applications.

Tensor based methods have found many applications in a number of scientific fields such as telecommunications, neuroscience, medicine and biology. The ability to express data forms in a high dimensional setting enables advanced processing and visualisation capabilities. Members of the engineering community and researchers in related areas from academia and industry are invited to participate in this interdisciplinary meeting and submit an abstract about their recent work if so they wish. A selection of abstracts will be scheduled for oral presentation and the rest will be invited to be presented as posters. (N.B., Posters previously presented in other scientific meetings are acceptable.)

The meeting will include (but not be limited to) the following areas:

  • Tensor factorisation and decomposition.
  • Tensor networks.
  • Dimensionality reduction.
  • Complex tensors.
  • Algorithms for tensor factorisation and decomposition.
  • Machine learning with tensor based methods.
  • Applications (in medicine, biology, neuroscience).

This meeting is free to attend but places are limited. Early registration is thus encouraged. Coffee breaks and lunch will be provided to all attendees.

Keynote Speakers:

  • Prof Rasmus Bro, University of Copenhagen.
  • Dr Saeid Sanei, University of Surrey.


Deadline for abstract submission: 28/Feb/2017

Registration deadline: 15/Mar/2017

Registration via: http://www.epay.ed.ac.uk/browse/extra_info.asp?compid=1&modid=2&deptid=24&catid=18&prodid=2479

For questions, write to the event contact email.

The organisers (Dr Loukianos Spyrou and Dr Javier Escudero) acknowledge the support of the EPSRC via the project EP/N014421/1.

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