Benoît Frénay‬

Constraint Enforcement on Decision Trees: A Survey

2022 · ACM Computing Surveys

Decision trees have the particularity of being machine learning models that are visually easy to interpret and understand. Therefore, they are primarily suited for sensitive domains like medical diagnosis, where decisions need to be explainable. …

Learning Customised Decision Trees for Domain-knowledge Constraints

2023 · Pattern Recognition

When applied to critical domains, machine learning models usually need to comply with prior knowledge and domain-specific requirements. For example, one may require that a learned decision tree model should be of limited size and …

An Experimental Investigation into the Evaluation of Explainability Methods

2023 · arXiv (Cornell University)

EXplainable Artificial Intelligence (XAI) aims to help users to grasp the reasoning behind the predictions of an Artificial Intelligence (AI) system. Many XAI approaches have emerged in recent years. Consequently, a subfield related to the …

Making Convolutional Neural Networks Energy-Efficient: An Introduction

2025

As convolutional neural networks (CNNs) have become mainstream for object recognition and image classification, the environmental impact caused by their high energy consumption (EC) is non negligible.This paper examines techniques that have the ability to …