266 citations · 325 across the 16 of their papers we have counts for
5 papers · 1 filter
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…
MUXConv: Information Multiplexing in Convolutional Neural Networks
Zhichao Lu, Kalyanmoy Deb, Vishnu Naresh Boddeti
Convolutional neural networks have witnessed remarkable improvements in computational efficiency in recent years. A key driving force has been the idea of trading-off model express…
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…