International E-Conference on Engineering, Technology and Management - ICETM 2020
Author(s) : Chao-Hsiang Hung, Hsin-Yu Chen, Kan-Lin Hsiung
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.