3 citations · 9 across the 10 of their papers we have counts for
9 papers · 1 filter
Predicting Public Health Impacts of Electricity Usage
Yejia Liu, Zhifeng Wu, Pengfei Li +1
The electric power sector is a leading source of air pollutant emissions, impacting the public health of nearly every community. Although regulatory measures have reduced air pollu…
Towards Vector Optimization on Low-Dimensional Vector Symbolic Architecture
Shijin Duan, Yejia Liu, Gaowen Liu +3
Vector Symbolic Architecture (VSA) is emerging in machine learning due to its efficiency, but they are hindered by issues of hyperdimensionality and accuracy. As a promising mitiga…
Building Socially-Equitable Public Models
Yejia Liu, Jianyi Yang, Pengfei Li +2
Public models offer predictions to a variety of downstream tasks and have played a crucial role in various AI applications, showcasing their proficiency in accurate predictions. Ho…
Scheduled Knowledge Acquisition on Lightweight Vector Symbolic Architectures for Brain-Computer Interfaces
Yejia Liu, Shijin Duan, Xiaolin Xu +1
Brain-Computer interfaces (BCIs) are typically designed to be lightweight and responsive in real-time to provide users timely feedback. Classical feature engineering is computation…
MetaLDC: Meta Learning of Low-Dimensional Computing Classifiers for Fast On-Device Adaption
Yejia Liu, Shijin Duan, Xiaolin Xu +1
Fast model updates for unseen tasks on intelligent edge devices are crucial but also challenging due to the limited computational power. In this paper,we propose MetaLDC, which met…
Navigating Memory Construction by Global Pseudo-Task Simulation for Continual Learning
Yejia Liu, Wang Zhu, Shaolei Ren
Continual learning faces a crucial challenge of catastrophic forgetting. To address this challenge, experience replay (ER) that maintains a tiny subset of samples from previous tas…