6 papers
Robust Optimization of Spring Design under Variable Manufacturing Tolerances
Grzegorz Sroka, Slawomir T. Wierzchon
A reliable assessment of an optimizer robustness requires tracking controlled changes in parameters to identify sources of algorithmic weakness. Such an approach was applied to the…
Sensitivity Analysis of the Transformation Using a Parameterized CEC 2017 Benchmark
Grzegorz Sroka, Sławomir T. Wierzchoń
CEC 2017 applies bias, shift and rotation simultaneously, obscuring their individual effects on algorithm behavior. We introduce a parameterized implementation controlling them ind…
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…