Conference Proceedings

International E-Conference on Engineering, Technology and Management - ICETM 2020

ON REALIZING ALTERNATING MINIMIZATION ALGORITHM WITH TENSORFLOW

Author(s) : Chao-Hsiang Hung, Hsin-Yu Chen, Kan-Lin Hsiung

Abstract

With the recent boom in big data analytics, many application areas require optimization algorithms that work at massive scale. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. In this note, we consider a distributed method for solving large-scale optimization problems called alternating minimization algorithm (AMA), and its implementation with TensorFlow is briefly reported.

Conference Title : International E-Conference on Engineering, Technology and Management - ICETM 2020
Conference Date(s) : 31, May 2020
Place : Online (Via Video Conference)
No fo Author(s) : 3
DOI : 10.15224/978-1-63248-188-7-20
Page(s) : 100
Electronic ISBN : 978-1-63248-188-7
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