Anaheim Convention Center
Anaheim, California, United States
26 - 30 April 2020
Conference SI110
Big Data II: Learning, Analytics, and Applications
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Abstract Due:
16 October 2019

Author Notification:
20 December 2019

Manuscript Due Date:
1 April 2020

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Conference Chair
Program Committee
Program Committee continued...
  • Dimitris A. Pados, Florida Atlantic Univ. (United States)
  • Piya Pal, Univ. of Maryland, College Park (United States)
  • Ashley Prater-Bennette, Air Force Research Lab. (United States)
  • Zhijun G. Qiao, The Univ. of Texas-Pan American (United States)
  • Ervin Sejdic, Univ. of Pittsburgh (United States)
  • Adrian Stern, Ben-Gurion Univ. of the Negev (Israel)
  • Yimin D. Zhang, Temple Univ. (United States)

Call for
With the information deluge resulting from ubiquitous communication, imaging, and surveillance devices, medical and e-commerce platforms, and social networking sites, big data analytics and learning are becoming increasingly important. The objective of this conference is to provide a consolidated forum to explore and promote advances in big data from learning, analytics, and application perspectives. Furthermore, it seeks to foster cross-fertilization of ideas across the various application areas of big data.

Original papers are solicited in, but not limited to, the following topical areas:
  • theoretical and physics-based modeling of big data systems
  • computational modeling and integration of big data
  • signal processing for big data
  • distributed sensing and processing for big data
  • big data science and analytics
  • visualization analytics for big data
  • machine learning for big data
  • hardware implementation of big data systems
  • compressive sensing techniques for big data analytics
  • energy-efficient big data systems
  • massive MIMO as big data systems
  • multi-function, multi-mission big data systems
  • big data for autonomous networked sensing
  • big data for imaging
  • big data for communications
  • big data in defense and security
  • big data in internet-of-things (IoT) and social networks
  • big data in medicine and biology.
Special Session on Tensor Methods for Signal Processing and Machine Learning
A special session on tensor methods for signal processing and machine learning is being planned. This session will focus on most recent advances in the theory and practice of tensor processing and analysis for a variety of applications.
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