Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152)

Authors Avrim Acar, Animashree Anandkumar, Lenore Mullin, Sebnem Rusitschka, Volker Tresp and all authors of the abstracts in this report



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Avrim Acar
Animashree Anandkumar
Lenore Mullin
Sebnem Rusitschka
Volker Tresp
and all authors of the abstracts in this report

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Avrim Acar, Animashree Anandkumar, Lenore Mullin, Sebnem Rusitschka, and Volker Tresp. Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152). In Dagstuhl Reports, Volume 6, Issue 4, pp. 57-79, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)
https://doi.org/10.4230/DagRep.6.4.57

Abstract

This report documents the program and the outcomes of Dagstuhl Perspectives Workshop 16152 "Tensor Computing for Internet of Things". In an interactive three-day workshop industrial and academic researchers exchanged their multidisciplinary perspectives through impulse talks, panel discussions, and break-out sessions. Internet of Things (IoT) or Cyber-physical systems (CPS) bring out interesting new challenges to tensor computing, such as the need for real-time analytics and control in interconnected dynamic networks, e.g. electricity, transportation, manufacturing. On the other hand, IoT/CPS have characteristics that make tensor methods applicable to extract information very efficiently. During our discussions we identified an action plan to have a structured approach that will enable the multidisciplinary community of domain and control experts, data scientists, and distributed, embedded software developers to share knowledge and best practices, compare and exchange tensor models depending on data types and applications in distinct IoT/CPS scenarios.
Keywords
  • Tensor Methods
  • Multi-way Data Analysis
  • Multi-linear Algebra
  • Tensor Software
  • Distributed \& Parallel Computing
  • Big Data Computing & Analytics
  • Cyber-physical Systems
  • Intelligent Autonomous Systems
  • Applications in Smart Grid
  • Mobility
  • Smart City

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