66 citations · 275 across the 22 of their papers we have counts for
6 papers · 1 filter
Complementary Ensemble Learning
Hung Nguyen, Morris Chang
To achieve high performance of a machine learning (ML) task, a deep learning-based model must implicitly capture the entire distribution from data. Thus, it requires a huge amount…
COVID-19 Pneumonia Severity Prediction using Hybrid Convolution-Attention Neural Architectures
Nam Nguyen, J. Morris Chang
This study proposed a novel framework for COVID-19 severity prediction, which is a combination of data-centric and model-centric approaches. First, we propose a data-centric pre-tr…
SEC-NoSQL: Towards Implementing High Performance Security-as-a-Service for NoSQL Databases
G. Dumindu Samaraweera, J. Morris Chang
During the last few years, the explosion of Big Data has prompted cloud infrastructures to provide cloud-based database services as cost effective, efficient and scalable solutions…
ESAI: Efficient Split Artificial Intelligence via Early Exiting Using Neural Architecture Search
Behnam Zeinali, Di Zhuang, J. Morris Chang
Recently, deep neural networks have been outperforming conventional machine learning algorithms in many computer vision-related tasks. However, it is not computationally acceptable…
A compressive multi-kernel method for privacy-preserving machine learning
Thee Chanyaswad, J. Morris Chang, S. Y. Kung
As the analytic tools become more powerful, and more data are generated on a daily basis, the issue of data privacy arises. This leads to the study of the design of privacy-preserv…
Generating Black-Box Adversarial Examples in Sparse Domain
Hadi Zanddizari, Behnam Zeinali, J. Morris Chang
Applications of machine learning (ML) models and convolutional neural networks (CNNs) have been rapidly increased. Although state-of-the-art CNNs provide high accuracy in many appl…