Implementing a Randomized SVD Algorithm and its Performance Analysis

Authors : Injamamul Haque Ahmed

Volume/Issue : Volume 6 - 2021, Issue 10 - October

Google Scholar :

Scribd :

Dimension reducing techniques are becoming more and more dominant in data science and model predictions because it is much more efficient and comfortable working on a small set of data than very large data. More often than not the reduced lower dimensional representation seems to contain the same properties as that of the higher dimensional space. Additionally, big sets of data prove to be a problem in terms of computational environment on both memory and processing power and hence the need for dimensionality reduction is key.


Paper Submission Last Date
28 - February - 2023

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.