Security at the physical layer (PHY) is a salient research topic in wireless systems, and
machine learning (ML) is emerging as a powerful tool for providing new data-driven security …

Hierarchical clustering is a recursive partitioning of a dataset into clusters at an increasingly
finer granularity. Motivated by the fact that most work on hierarchical clustering was based …

Abstract Similarity-based Hierarchical Clustering (HC) is a classical unsupervised machine
learning algorithm that has traditionally been solved with heuristic algorithms like Average …

Hierarchical clustering is a data analysis method that has been used for decades. Despite its
widespread use, the method has an underdeveloped analytical foundation. Having a well …

Hierarchical clustering is typically performed using algorithmic-based optimization searching
over the discrete space of trees. While these optimization methods are often effective, their …

As machine learning has become more prevalent, researchers have begun to recognize the
necessity of ensuring machine learning systems are fair. Recently, there has been an …

Vessel trajectory clustering, a crucial component of the maritime intelligent transportation
systems, provides valuable insights for applications such as anomaly detection and …

The applicability of agglomerative clustering, for inferring both hierarchical and flat
clustering, is limited by its scalability. Existing scalable hierarchical clustering methods …

We study the widely-used hierarchical agglomerative clustering (HAC) algorithm on edge-
weighted graphs. We define an algorithmic framework for hierarchical agglomerative graph …

Hierarchical clustering over graphs is a fundamental task in data mining and machine
learning with applications in many domains including phylogenetics, social network …