309 citations · 669 across the 15 of their papers we have counts for
15 papers
An Interactive Knowledge-based Multi-objective Evolutionary Algorithm Framework for Practical Optimization Problems
Abhiroop Ghosh, Kalyanmoy Deb, Erik Goodman +1
Experienced users often have useful knowledge and intuition in solving real-world optimization problems. User knowledge can be formulated as inter-variable relationships to assist…
Enhanced Innovized Repair Operator for Evolutionary Multi- and Many-objective Optimization
Sukrit Mittal, Dhish Kumar Saxena, Kalyanmoy Deb +1
"Innovization" is a task of learning common relationships among some or all of the Pareto-optimal (PO) solutions in multi- and many-objective optimization problems. Recent studies…
NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search
Zhichao Lu, Kalyanmoy Deb, Erik Goodman +2
In this paper, we propose an efficient NAS algorithm for generating task-specific models that are competitive under multiple competing objectives. It comprises of two surrogates, o…
Neural Architecture Transfer
Zhichao Lu, Gautam Sreekumar, Erik Goodman +3
Neural architecture search (NAS) has emerged as a promising avenue for automatically designing task-specific neural networks. Existing NAS approaches require one complete search fo…
It is Time for New Perspectives on How to Fight Bloat in GP
Francisco Fernández de Vega, Gustavo Olague, Francisco Chávez +3
The present and future of evolutionary algorithms depends on the proper use of modern parallel and distributed computing infrastructures. Although still sequential approaches domin…
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…