6 papers
Composite Silhouette: A Subsampling-based Aggregation Strategy
Aggelos Semoglou, Aristidis Likas, John Pavlopoulos
Determining the number of clusters is a central challenge in unsupervised learning, where ground-truth labels are unavailable. The Silhouette coefficient is a widely used internal…
TopClustRAG at SIGIR 2025 LiveRAG Challenge
Juli Bakagianni, John Pavlopoulos, Aristidis Likas
We present TopClustRAG, a retrieval-augmented generation (RAG) system developed for the LiveRAG Challenge, which evaluates end-to-end question answering over large-scale web corpor…
Silhouette-Driven Instance-Weighted -means
Aggelos Semoglou, Aristidis Likas, John Pavlopoulos
Clustering is a fundamental unsupervised learning task with applications across a wide range of domains. Popular algorithms such as -means are efficient and widely used, but can…
Universal description of the Neutron Star's surface and its key global properties: A Machine Learning Approach for nonrotating and rapidly rotating stellar models
Grigorios Papigkiotis, Georgios Vardakas, Aristidis Likas +1
Neutron stars provide an ideal theoretical framework for exploring fundamental physics when nuclear matter surpasses densities encountered within atomic nuclei. Despite their param…
Counterfactual Explanations for k-means and Gaussian Clustering
Georgios Vardakas, Antonia Karra, Evaggelia Pitoura +1
Counterfactuals have been recognized as an effective approach to explain classifier decisions. Nevertheless, they have not yet been considered in the context of clustering. In this…
Statistical Modeling of Univariate Multimodal Data
Paraskevi Chasani, Aristidis Likas
Unimodality constitutes a key property indicating grouping behavior of the data around a single mode of its density. We propose a method that partitions univariate data into unimod…