2 citations · 2 across the 4 of their papers we have counts for
4 papers
A Computing-in-Memory-based One-Class Hyperdimensional Computing Model for Outlier Detection
Ruixuan Wang, Sabrina Hassan Moon, Xiaobo Sharon Hu +2
In this work, we present ODHD, an algorithm for outlier detection based on hyperdimensional computing (HDC), a non-classical learning paradigm. Along with the HDC-based algorithm,…
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…
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…