ABSTRACT: In this paper, an Optimal Predictive Modeling of Nonlinear Transformations “OPMNT” method has been developed while using Orthogonal Nonnegative Matrix Factorization “ONMF” with the ...

Abstract: Matrix factorization is a central paradigm in matrix completion and collaborative filtering. Low-rank factorizations have been extremely successful in reconstructing and generalizing ...

Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the ...

String manipulation is a core skill for every Python developer. Whether you’re working with CSV files, log entries, or text analytics, knowing how to split strings in Python makes your code cleaner ...

Multiplication in Python may seem simple at first—just use the * operator—but it actually covers far more than just numbers. You can use * to multiply integers and floats, repeat strings and lists, or ...

Numerical linear algebra for quaternions — fast, practical, and well‑tested. QuatIca was inspired by the pioneering work in quaternion linear algebra, particularly the QTFM (Quaternion Toolbox for ...

In this tutorial, we delve into the creation of an intelligent Python-to-R code converter that integrates Google’s free Gemini API for validation and improvement suggestions. We start by defining the ...

Click to share on X (Opens in new window) X Click to share on Facebook (Opens in new window) Facebook Michael ends up finding himself trapped on the roof of his school with the Agents closing in on ...

Abstract: Multi-layered graphs are popular in mobility studies because transportation data include multiple modalities, such as railways, buses, and taxis. Another example of a multi-layered graph is ...

As AI engineers, crafting clean, efficient, and maintainable code is critical, especially when building complex systems. Let’s explore some key design patterns that are particularly useful in AI and ...