Abstract: The traditional K-means algorithm often leads to unstable clustering quality due to the randomness of the initial clustering center selection and tends to fall into suboptimal solutions when ...

Mr. Means quietly departed his federal role about a month ago. His sister has been nominated for surgeon general. By Benjamin Mueller Calley Means, an influential adviser to Health Secretary Robert F.

Rocky high steep slopes are among the most dangerous disaster-causing geological bodies in large-scale engineering projects, like water conservancy and hydropower projects, railway tunnels, and metal ...

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

This project is my independent research into SAT solvers written entirely in Python, designed to explore the theory and practice of propositional satisfiability. It begins with a baseline DPLL ...

Accurately identifying fracture zones and their types in strata is of great significance for enhancing oil and gas recovery efficiency. Due to its complicated geological structure and long-term ...

What if you could create your very own personal AI assistant—one that could research, analyze, and even interact with tools—all from scratch? It might sound like a task reserved for seasoned ...

Implement the K-Means Clustering algorithm from scratch using NumPy and visualize the results with Matplotlib. Why it's a good addition: It's a foundational unsupervised learning algorithm that fits ...

Amsterdam’s struggles with its welfare fraud algorithm show us the stakes of deploying AI in situations that directly affect human lives. What Amsterdam’s welfare fraud algorithm taught me about fair ...

Learn how the Adadelta optimization algorithm really works by coding it from the ground up in Python. Perfect for ML enthusiasts who want to go beyond the black box! Florida State Bracing for Hefty ...

Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering algorithms to a ...