The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy
  • Promote your Publication

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Joint Deep Clustering: Classification and Review

Author 1: Arwa Alturki
Author 2: Ouiem Bchir
Author 3: Mohamed Maher Ben Ismail

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0121096

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 10, 2021.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Clustering is a fundamental problem in machine learning. To address this, a large number of algorithms have been developed. Some of these algorithms, such as K-means, handle the original data directly, while others, such as spectral clustering, apply linear transformation to the data. Still others, such as kernel-based algorithms, use nonlinear transformation. Since the performance of the clustering depends strongly on the quality of the data representation, representation learning approaches have been extensively researched. With the recent advances in deep learning, deep neural networks are being increasingly utilized to learn clustering-friendly representation. We provide here a review of existing algorithms that are being used to jointly optimize deep neural networks and clustering methods.

Keywords: Clustering; deep learning; deep neural network; representation learning; clustering loss; reconstruction loss

Arwa Alturki, Ouiem Bchir and Mohamed Maher Ben Ismail, “Joint Deep Clustering: Classification and Review” International Journal of Advanced Computer Science and Applications(IJACSA), 12(10), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0121096

@article{Alturki2021,
title = {Joint Deep Clustering: Classification and Review},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0121096},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0121096},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {10},
author = {Arwa Alturki and Ouiem Bchir and Mohamed Maher Ben Ismail}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2023

2-3 March 2023

  • Virtual

Computing Conference 2023

22-23 June 2023

  • London, United Kingdom

IntelliSys 2023

7-8 September 2023

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2023

2-3 November 2023

  • San Francisco, United States
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org