Abstract: Conventional soft clustering algorithms perform well on linearly distributed features, but their performance degrades on nonlinearly distributed features in high-dimensional space. In this ...

XRP $2 support has structural backing this time: 1.35B tokens moved into ETF custody, whales accumulated 340M XRP, and exchange balances dropped 45%—creating supply squeeze that repeatedly defended $2 ...

Automated apple harvesting is hindered by clustered fruits, varying illumination, and inconsistent depth perception in complex orchard environments. While deep learning models such as Faster R-CNN and ...

Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock prices under the condition that market is efficient. In most ...

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 ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Clustering techniques are consolidated as a powerful strategy for analyzing the ...

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, ...

Researchers have developed a new AI algorithm, called Torque Clustering, that significantly improves how AI systems independently learn and uncover patterns in data, without human guidance.

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, ...