71 citations · 109 across the 5 of their papers we have counts for
5 papers
Towards Interpretable-AI Policies Induction using Evolutionary Nonlinear Decision Trees for Discrete Action Systems
Yashesh Dhebar, Kalyanmoy Deb, Subramanya Nageshrao +2
Black-box AI induction methods such as deep reinforcement learning (DRL) are increasingly being used to find optimal policies for a given control task. Although policies represente…
Evaluating Nonlinear Decision Trees for Binary Classification Tasks with Other Existing Methods
Yashesh Dhebar, Sparsh Gupta, Kalyanmoy Deb
Classification of datasets into two or more distinct classes is an important machine learning task. Many methods are able to classify binary classification tasks with a very high a…
Interpretable Rule Discovery Through Bilevel Optimization of Split-Rules of Nonlinear Decision Trees for Classification Problems
Yashesh Dhebar, Kalyanmoy Deb
For supervised classification problems involving design, control, other practical purposes, users are not only interested in finding a highly accurate classifier, but they also dem…
Multi-Objective Evolutionary Design of Deep Convolutional Neural Networks for Image Classification
Zhichao Lu, Ian Whalen, Yashesh Dhebar +4
Early advancements in convolutional neural networks (CNNs) architectures are primarily driven by human expertise and by elaborate design processes. Recently, neural architecture se…
NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm
Zhichao Lu, Ian Whalen, Vishnu Boddeti +4
This paper introduces NSGA-Net -- an evolutionary approach for neural architecture search (NAS). NSGA-Net is designed with three goals in mind: (1) a procedure considering multiple…