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 ...

A vast region of our solar system, called the Kuiper belt, stretches from the orbit of Neptune out to 50 or so astronomical units (AU), where an AU is the distance between Earth and the sun. This ...

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Trump administration looking to sell ...

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 ...

Spotware, the developer of the cTrader multi-asset trading platform has launched an essential update with the introduction of cTrader Windows version 5.4, native Python, supporting algorithmic trading ...

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 ...