Technological advancement has enabled us to store and process huge amount of data in
relatively short spans of time. The nature of data is rapidly changing, particularly its …

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

Obtaining scalable algorithms for\emph {hierarchical agglomerative clustering}(HAC) is of
significant interest due to the massive size of real-world datasets. At the same time …

We consider the widely-used average-linkage, single-linkage, and Ward's methods for
computing hierarchical clusterings of high-dimensional Euclidean inputs. It is easy to show …

We initiate a comprehensive experimental study of objective-based hierarchical clustering
methods on massive datasets consisting of deep embedding vectors from computer vision …

We present PSEUDo, a visual pattern retrieval tool for multivariate time series. It aims to
overcome the uneconomic (re-) training problem accompanying deep learning-based …

This paper studies the hierarchical clustering problem, where the goal is to produce a
dendrogram that represents clusters at varying scales of a data set. We propose the …

The significant increase in the volume of fake (spam) messages has led to an urgent need to
develop and implement a robust anti‐spam method. Several of the current anti‐spam …

Driven by the automation technologies and health informatics of Industry 4.0, hospitals in
China have deployed a complete automation system/platform for healthcare services …

Given recording pairwise distances, the Metric Violation Distance problem asks to compute
the distance between and the metric cone; ie, modify the minimum number of entries of to …