Abstract: The density peaks clustering (DPC) algorithm is a density-based clustering method that effectively identifies clusters with uniform densities. However, if the datasets have uneven density, ...

Abstract: Most clustering algorithms require setting one or more parameters, which rely on prior knowledge or are constantly adjusted based on external indicators. To address the issues of requiring ...

In structural health monitoring (SHM), uncertainties from environmental noise and modeling errors affect damage detection accuracy. This paper introduces a new concept: the Fast Fourier Transform ...

1 School of Computer Science and Technology, Yibin University, Yibin, China 2 School of Computer and Software, Southwest Petroleum University, Chengdu, China Ever since Density Peak Clustering (DPC) ...

I’ve observed an unexpected result when comparing direct clustering using CD-HIT at 40% threshold versus hierarchical clustering down to 30%. Direct clustering (-c 0.4): I have directly used cd-hit to ...

Department of Chemistry, University of Florida, Gainesville, Florida 32611, United States Quantum Theory Project, University of Florida, Gainesville, Florida 32611, United States ...

Aligning large language models (LLMs) with human values remains difficult due to unclear goals, weak training signals, and the complexity of human intent. Direct Alignment Algorithms (DAAs) offer a ...

University of Bremen, Institute for Physical and Theoretical Chemistry, Leobener Str. 6, D-28359 Bremen, Germany Bremen Center for Computational Materials Science, University of Bremen, Am Fallturm 1, ...