An Efficient FPGA-Based Hardware Accelerator for Convex Optimization-Based SVM Classifier for Machine Learning on Embedded Platforms

An Efficient FPGA-Based Hardware Accelerator for Convex Optimization-Based SVM Classifier for Machine Learning on Embedded Platforms

Machine learning is becoming the cornerstones of smart and autonomous systems. Machine learning algorithms can be categorized into supervised learning (classification) and unsupervised learning (clustering). Among many classification algorithms, the Support Vector Machine (SVM) classifier is one of...

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Bibliographic Details
Main Authors: Srikanth Ramadurgam, Darshika G. Perera
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Electronics
Subjects:
FPGAs
hardware accelerators
embedded architectures
machine learning
convex optimization
Support Vector Machines
Online Access:https://www.mdpi.com/2079-9292/10/11/1323

Internet

https://www.mdpi.com/2079-9292/10/11/1323

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