Project overview
The widespread use of multisensor technology and the emergence of big data sets have highlighted
the limitations of standard flat-view matrix models and the necessity to move toward more versatile
data analysis tools. It is therefore both timely and important to be acquainted with the most
recent advances in analysis of huge multi-dimensional arrays (tensors) of data and to be equipped
with the appropriate tools. To this end, the tutorial will be divided in two parts:
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The first half will be a classic lecture-type tutorial which will start with the Curse of Dimansionality in Big Data analytics, in the form of the four V’s: Volume, Variety,
Velocity, Veracity. This will be followed by a comprehensive overview of tensor decompositions, supported by a variety of examples. Overall, a whole spectrum of tensor applications will be covered, from the basics of Big Data to feasible realizations through multi-linear algebra and tensor networks.
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The second half will be a hands-on demo based on our open source software, HOTTBOX, specifically developed for preforming decompositions, visualisation and analysis of multidimensional data. All demonstrations material, as well as exercises, will be provided in the form of the Jupyter notebooks, the most popular interactive environment for exploratory data analysis. Local installation of additional software will be optional, as all examples can be seamlessly run in the Cloud.
This two-part structure will make this tutorial suitable for the multidisciplinary machine learning and data analytic communities, together with offering the attendees an enhanced experience and a hands-on insight into immediate practical aspects and impact of the tensor technology.
