26 citations · 41 across the 10 of their papers we have counts for
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cs.LG2019★ 6 cited
Adversarial Deep Embedded Clustering: on a better trade-off between Feature Randomness and Feature Drift
Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini
Clustering using deep autoencoders has been thoroughly investigated in recent years. Current approaches rely on simultaneously learning embedded features and clustering the data po…
cs.LG2019
Deep Clustering with a Dynamic Autoencoder: From Reconstruction towards Centroids Construction
Nairouz Mrabah, Naimul Mefraz Khan, Riadh Ksantini +1
In unsupervised learning, there is no apparent straightforward cost function that can capture the significant factors of variations and similarities. Since natural systems have smo…