arXiv Machine Learning
Jul 28
The K-SCAN Clustering Algorithm
arXiv:2607. 24537v1 Announce Type: new Abstract: In the Big Data era, the scalability of clustering algorithms constitutes a key challenge.
Persistent Multiscale Density-based Clustering
arXiv:2512. 16558v3 Announce Type: replace Abstract: Clustering is a cornerstone of modern data analysis.
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arXiv Machine Learning
Jul 22
Topology-Driven Clustering: Enhancing Performance with Betti Number Filtration
arXiv:2505. 04346v2 Announce Type: replace Abstract: Clustering aims at partitioning data points into groups of similar objects without knowing about the class labels.
arXiv AI
Aug 10
Density-aware Hierarchical Clustering Based on Element-Categorized Connection Subgraphs
arXiv:2608. 06990v1 Announce Type: cross Abstract: Clustering is a fundamental data mining technique for pattern recognition through unsupervised learning.
arXiv Machine Learning
Jun 2
Cluster Analysis with Resampling for Validation and Exploration (CARVE)
arXiv:2606. 00327v1 Announce Type: cross Abstract: Clustering is widely used across the sciences as the foundation for downstream data-driven scientific discoveries.
arXiv Machine Learning
Jul 21
Preserving Clusters in Error-Bounded Lossy Compression of Scientific Particle Data
arXiv:2604. 18801v2 Announce Type: replace Abstract: Scientific particle simulations in cosmology, molecular dynamics, and fluid dynamics produce large-scale datasets whose storage, movement, and analysis increasingly rely on lossy compression.
arXiv Machine Learning
Jun 3
ExDBSCAN: Explaining DBSCAN with Counterfactual Reasoning -- Additional Material
arXiv:2605. 30225v2 Announce Type: replace Abstract: Clustering is an unsupervised technique for grouping data points by similarity.
arXiv Machine Learning
Jun 5
Central Description Length (CDL) Clustering Validation Index
arXiv:2606. 05230v1 Announce Type: cross Abstract: Selecting a clustering algorithm and its hyperparameters without labels is a common difficulty in engineering machine learning pipelines that work with unsupervised analysis of sensor, image, or process data.
arXiv Machine Learning
Jul 3
Scalable and Distributed Silhouette Approximation
arXiv:2607. 01993v1 Announce Type: cross Abstract: The silhouette is one of the most widely used measures to assess the quality of a $k$-clustering of a dataset of $n$ elements.
arXiv Machine Learning
Jul 13
Scalable Varied-Density Clustering via Graph Propagation
arXiv:2508. 02989v2 Announce Type: replace Abstract: We propose a novel perspective on varied-density clustering for high-dimensional data by framing it as a label propagation process in neighborhood graphs that adapt to local density variations.
arXiv Machine Learning
Jun 18
FOSC-X: An Extended Framework for Optimal Local Cuts and Non-Horizontal Cluster Selection from Clustering Hierarchies
arXiv:2606. 18972v1 Announce Type: cross Abstract: Extracting a flat clustering solution from a hierarchy is a common task in practical cluster analysis and can be formulated as an optimisation problem.
arXiv Machine Learning
Jul 28
Why does Greedy Search produce Optimal Clustering Outcomes? A Fixed-Core Assignment Theory
arXiv:2607. 24237v1 Announce Type: new Abstract: Many existing clustering methods are designed based on a set-oriented definition---a cluster is a set of similar points---relying a point-to-point similarity function to find similar points.
arXiv Machine Learning
Jun 30
Minimum Description Length based Granular-Ball Tree Regularization for Spectral Clustering
arXiv:2605. 22410v2 Announce Type: replace Abstract: Spectral clustering largely depends on the affinity graph, yet constructing a graph that preserves reliable local connectivity while adapting to heterogeneous data structures remains challenging.