A new Riemannian framework called HyperSpectrum Geometry lets text classifiers bend the curvature of their semantic space, ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Feature selection (FS) is a critical step in hyperspectral image (HSI) classification, essential for reducing data dimensionality while preserving classification accuracy. However, FS for HSIs remains ...

Amin's research applies AI and machine learning especially multimodal, text, unsupervised, and graph-based methods to turn ...

I often hear people say, "I want to study machine learning, but I don't know where to start." Some open a book on mathematical formulas only to close it immediately, while others burn out just trying ...

Why accuracy and strong backtests can mislead in ML—and why reproducibility, leakage-safe validation, and economic evidence ...