5 citations · 9 across the 8 of their papers we have counts for
8 papers
Evaluating and Enhancing Robustness of Deep Recommendation Systems Against Hardware Errors
Dongning Ma, Xun Jiao, Fred Lin +5
Deep recommendation systems (DRS) heavily depend on specialized HPC hardware and accelerators to optimize energy, efficiency, and recommendation quality. Despite the growing number…
PyGFI: Analyzing and Enhancing Robustness of Graph Neural Networks Against Hardware Errors
Ruixuan Wang, Fred Lin, Daniel Moore +2
Graph neural networks (GNNs) have recently emerged as a promising learning paradigm in learning graph-structured data and have demonstrated wide success across various domains such…
NasHD: Efficient ViT Architecture Performance Ranking using Hyperdimensional Computing
Dongning Ma, Pengfei Zhao, Xun Jiao
Neural Architecture Search (NAS) is an automated architecture engineering method for deep learning design automation, which serves as an alternative to the manual and error-prone p…
Hyperdimensional Computing vs. Neural Networks: Comparing Architecture and Learning Process
Dongning Ma, Xun Jiao
Hyperdimensional Computing (HDC) has obtained abundant attention as an emerging non von Neumann computing paradigm. Inspired by the way human brain functions, HDC leverages high di…
EnHDC: Ensemble Learning for Brain-Inspired Hyperdimensional Computing
Ruixuan Wang, Dongning Ma, Xun Jiao
Ensemble learning is a classical learning method utilizing a group of weak learners to form a strong learner, which aims to increase the accuracy of the model. Recently, brain-insp…
Automated Architecture Search for Brain-inspired Hyperdimensional Computing
Junhuan Yang, Yi Sheng, Sizhe Zhang +6
This paper represents the first effort to explore an automated architecture search for hyperdimensional computing (HDC), a type of brain-inspired neural network. Currently, HDC des…
Deep Learning Based Walking Tasks Classification in Older Adults using fNIRS
Dongning Ma, Meltem Izzetoglu, Roee Holtzer +1
Decline in gait features is common in older adults and an indicator of increased risk of disability, morbidity, and mortality. Under dual task walking (DTW) conditions, further deg…
AMITE: A Novel Polynomial Expansion for Analyzing Neural Network Nonlinearities
Mauro J. Sanchirico, Xun Jiao, C. Nataraj
Polynomial expansions are important in the analysis of neural network nonlinearities. They have been applied thereto addressing well-known difficulties in verification, explainabil…