23 citations · 23 across the 8 of their papers we have counts for
8 papers
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_…
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…
SCoNE: Spherical Consistent Neighborhoods Ensemble for Effective and Efficient Multi-View Anomaly Detection
Yang Xu, Hang Zhang, Yixiao Ma +2
The core problem in multi-view anomaly detection is to represent local neighborhoods of normal instances consistently across all views. Recent approaches consider a representation…
An Online Automatic Modulation Classification Scheme Based on Isolation Distributional Kernel
Xinpeng Li, Zile Jiang, Kai Ming Ting +1
Automatic Modulation Classification (AMC), as a crucial technique in modern non-cooperative communication networks, plays a key role in various civil and military applications. How…
RAD: A Realistic Multi-View Benchmark for Pose-Agnostic Anomaly Detection
Kaichen Zhou, Xinhai Chang, Taewhan Kim +8
Anomaly detection is essential for robotic perception and industrial inspection, yet most benchmarks are collected under controlled conditions with fixed viewpoints and stable illu…
Distributed Clustering based on Distributional Kernel
Hang Zhang, Yang Xu, Lei Gong +2
This paper introduces a new framework for clustering in a distributed network called Distributed Clustering based on Distributional Kernel (K) or KDC that produces the final cluste…
Anomaly Detection Based on Isolation Mechanisms: A Survey
Yang Cao, Haolong Xiang, Hang Zhang +2
Anomaly detection is a longstanding and active research area that has many applications in domains such as finance, security, and manufacturing. However, the efficiency and perform…
Distribution-Based Trajectory Clustering
Zi Jing Wang, Ye Zhu, Kai Ming Ting
Trajectory clustering enables the discovery of common patterns in trajectory data. Current methods of trajectory clustering rely on a distance measure between two points in order t…