A Method To Generate Predictor Circuits For The Classification Of Tabular Data

Researchers have developed a machine learning-based method to automatically generate classification circuits from tabular data, which can be used to improve the efficiency of deep learning models. This approach, known as “tiny classifiers,” aims to minimize the memory and area footprint of trained models for deployment on various hardware accelerators.