Deep Clustering (A Self-Supervised Learning System)

If you are interested in any of the following,

1. How do I develop a deep learning model, that can learn to do clustering?
2. How to effectively utilize the massive amount of unlabeled data generated every day??
3. How do I get something meaningful from raw or unlabeled data?
4. What is a Self-Supervised deep learning system??
5. Facing trouble understanding the state of the arts in this area?

Then this article is for you.

Another important thing is that the quick availability of open-source coding and libraries has effectively supported the rapid growth of deep learning. I mean to say that once you are able to understand these concepts, tones of libraries and resources are already available to use these techniques.

The following contains a detailed discussion about Deep Clustering (a self-supervised algorithm) and some tips to go through research work in this area.

#deeplearning #selfsupervised #deepclustering #artficialintelligence #artificialneuralnetworks #classification

Reference.

1. Caron, Mathilde, Piotr Bojanowski, Armand Joulin, and Matthijs Douze. "Deep clustering for unsupervised learning of visual features." In Proceedings of the European conference on computer vision (ECCV), pp. 132-149. 2018.

2. Bo, Deyu, Xiao Wang, Chuan Shi, Meiqi Zhu, Emiao Lu, and Peng Cui. "Structural deep clustering network." In Proceedings of the web conference 2020, pp. 1400-1410. 2020.

3. Lara, Juan S., and Fabio A. González. "Dissimilarity mixture autoencoder for deep clustering." arXiv preprint arXiv:2006.08177 (2020).

4. Zhan, Xiaohang, Jiahao Xie, Ziwei Liu, Yew-Soon Ong, and Chen Change Loy. "Online deep clustering for unsupervised representation learning." In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp. 6688-6697. 2020.

5. Yang, Xu, Cheng Deng, Kun Wei, Junchi Yan, and Wei Liu. "Adversarial learning for robust deep clustering." Advances in Neural Information Processing Systems 33 (2020): 9098-9108.

6. Min, Erxue, Xifeng Guo, Qiang Liu, Gen Zhang, Jianjing Cui, and Jun Long. "A survey of clustering with deep learning: From the perspective of network architecture." IEEE Access 6 (2018): 39501-39514.

7. Chen, Minhua, Badrinath Jayakumar, Padmasundari Gopalakrishnan, Qiming Huang, Michael Johnston, and Patrick Haffner. "Deep Clustering with Measure Propagation." arXiv preprint arXiv:2104.08967 (2021).

8. Guo, Wengang, Kaiyan Lin, and Wei Ye. "Deep embedded K-means clustering." In 2021 International Conference on Data Mining Workshops (ICDMW), pp. 686-694. IEEE, 2021.