36 citations · 52 across the 3 of their papers we have counts for
3 papers
cs.CV2024
Clustering-friendly Representation Learning for Enhancing Salient Features
Toshiyuki Oshima, Kentaro Takagi, Kouta Nakata
Recently, representation learning with contrastive learning algorithms has been successfully applied to challenging unlabeled datasets. However, these methods are unable to disting…
cs.LG2021★ 36 cited
Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation
Yaling Tao, Kentaro Takagi, Kouta Nakata
Clustering is one of the most fundamental tasks in machine learning. Recently, deep clustering has become a major trend in clustering techniques. Representation learning often play…
cs.LG2018★ 16 cited
RDEC: Integrating Regularization into Deep Embedded Clustering for Imbalanced Datasets
Yaling Tao, Kentaro Takagi, Kouta Nakata
Clustering is a fundamental machine learning task and can be used in many applications. With the development of deep neural networks (DNNs), combining techniques from DNNs with clu…