Approximate computing for machine learning

Approximate Computing has emerged as a promising paradigm to enhance computational efficiency by introducing controlled inaccuracies in arithmetic operations. This study explores the application of static approximate adders (AAs) within a machine learning context, specifically the K-means clus...

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Bibliographic Details
Main Author: Syed Mohammed Mosayeeb Al Hady Zaheen
Other Authors: Douglas Maskell
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2025
Subjects:
Online Access:https://hdl.handle.net/10356/183990
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Institution: Nanyang Technological University
Language: English