5 papers
Sensitivity of hMPA to Controlled CEC 2017 Transformations
Grzegorz Sroka, Sławomir T. Wierzchoń
The standard CEC 2017 benchmark applies bias, shift, and rotation simultaneously, confounding their individual effects on algorithmic behavior. We introduce a parameterized impleme…
Rough Sets for Explainability of Spectral Graph Clustering
Bartłomiej Starosta, Sławomir T. Wierzchoń, Piotr Borkowski +4
Graph Spectral Clustering methods (GSC) allow representing clusters of diverse shapes, densities, etc. However, the results of such algorithms, when applied e.g. to text documents,…
Robustness and Invariance of Hybrid Metaheuristics under Objective Function Transformations
Grzegorz Sroka, Sławomir T. Wierzchoń
This paper evaluates the robustness and structural invariance of hybrid population-based metaheuristics under various objective space transformations. A lightweight plug-and-play h…
Explainable Graph Spectral Clustering For GloVe-like Text Embeddings
Mieczysław A. Kłopotek, Sławomir T. Wierzchoń, Bartłomiej Starosta +3
In a previous paper, we proposed an introduction to the explainability of Graph Spectral Clustering results for textual documents, given that document similarity is computed as cos…
A Method for Handling Negative Similarities in Explainable Graph Spectral Clustering of Text Documents -- Extended Version
Mieczysław A. Kłopotek, Sławomir T. Wierzchoń, Bartłomiej Starosta +2
This paper investigates the problem of Graph Spectral Clustering with negative similarities, resulting from document embeddings different from the traditional Term Vector Space (li…