3 papers
cs.LG2026
Learning to Unlearn: Machine Unlearning via Learning the Unlearning Behaviors
Hang Zhang, Kaifeng Zhang, Yixiao Ma +3
Various machine unlearning techniques have been developed in response to privacy legislation requirements, enabling individuals to exercise their legal right to have their data $D_…
cs.LG2026
How to Achieve the Intended Aim of Deep Clustering Now, without Deep Learning
Kai Ming Ting, Wei-Jie Xu, Hang Zhang
Deep clustering (DC) is often quoted to have a key advantage over -means clustering. Yet, this advantage is often demonstrated using image datasets only, and it is unclear wheth…
stat.ML2026
Mass Distribution versus Density Distribution in the Context of Clustering
Kai Ming Ting, Ye Zhu, Hang Zhang +1
This paper investigates two fundamental descriptors of data, i.e., density distribution versus mass distribution, in the context of clustering. Density distribution has been the de…