Abstract: In multi-label learning, each instance in the training set is associated with a set of labels, and the task is to output a label set whose size is unknown a priori for each unseen instance.

The CPU and GPU confusion matrices are nearly identical. The prediction agreement between both implementations reached 99.82%, showing that the CUDA implementation preserved the classification ...

Abstract: Visible light positioning (VLP) has become one of the promising solutions in the field of indoor positioning applications, due to its high positioning accuracy, low implementation cost, and ...

This project uses Machine Learning to classify Iris flowers into three different species based on their physical measurements. The classification is performed using the K-Nearest Neighbors (KNN) ...

The emerging convergence of AI-first design principles and environmental consciousness is reshaping how we think about ...

The primary endpoint was 3-month mortality due to all causes. Six ML algorithms (Extreme Gradient Boosting [XGBoost], logistic regression (LR), Light Gradient Boosting Machine [LightGBM], random ...

What about ChatGPT and related large AI Systems? How will they impact us all? As a longtime researcher in AI, I'm excited about the ways in which these new AI systems can improve our healthcare, ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...