GlobalSIP 2018:

Tensor Methods for Signal Processing and Machine Learning

[Download the PDF Call for Papers]

Tensor methods have been attracting increasing documented interest over the past decade, finding a plethora of important signal processing, data analysis, and machine learning applications. Tensors have been extensively employed in several research areas such as computer vision, chemometrics, bioinformatics, communications, array processing, network analysis, data mining, and deep learning, among others. The wide success of tensor methods can be attributed to their inherent ability to better model, analyze, predict, recognize, and learn from multi-modal data. This symposium wishes to serve as a global forum for researchers to meet, exchange ideas, and present new theoretical and algorithmic findings related to tensor methods. Based on broad signal processing and machine learning foundations, this symposium aspires to foster interdisciplinary discussions and bring together researchers from both academia and the industry.

Submissions are welcome on topics including:

Paper Submission

Prospective authors are invited to submit full-length papers (up to 4 pages for technical content including figures and possible references, and with one additional optional 5th page containing only references) and extended abstracts (up to 2 pages, for paper-less industry presentations and Ongoing Work presentations).. Manuscripts should be original (not submitted/published anywhere else) and written in accordance with the standard IEEE double-column paper template. Accepted full-length papers will be indexed on IEEE Xplore. Accepted abstracts will not be indexed in IEEE Xplore, however the abstracts and/or the presentations will be included in the IEEE SPS SigPort. Accepted papers and abstracts will be scheduled in lecture and poster sessions.

Important Dates

Paper Submission DeadlineJune 17, 2018 June 29, 2018
Review Results AnnouncedAugust 7, 2018
Camera-Ready Papers DueAugust 22, 2018

Organizing Committee

General Chairs

Technical Program Chairs

Technical Program Committee