4 citations · 4 across the 6 of their papers we have counts for
6 papers
Potentials and Limitations on Different Busbar Protections in Industrial Applications
Karl M. H. Lai, Yunhe Hou, Kwunhang Wong
Busbar protection is a cornerstone of industrial power system reliability, as failures at switchgear can propagate rapidly and extend restoration times. The Taiwan "303 blackout" i…
RRAM-DP: Device-Calibrated Differential Privacy for In-Memory Edge Learning
Kwunhang Wong, Jichang Yang, Karl M. H. Lai +7
Edge Artificial Intelligence of Things (AIoT) systems often collect sensitive data in situ, raising serious privacy concerns. Resistive-switching random-access memory (RRAM) is an…
Towards Secure and Efficient DNN Accelerators via Hardware-Software Co-Design
Wei Xuan, Zihao Xuan, Rongliang Fu +8
The rapid deployment of deep neural network (DNN) accelerators in safety-critical domains such as autonomous vehicles, healthcare systems, and financial infrastructure necessitates…
Parameter Efficient Machine Unlearning on Hybrid Resistive Memory based Compute-in-Memory Accelerators
Ning Lin, Jichang Yang, Yangu He +17
Resistive memory compute-in-memory accelerators provide energy efficient analogue matrix vector multiplication for neural network inference, but frequent reprogramming of analogue…
SNNGX: Securing Spiking Neural Networks with Genetic XOR Encryption on RRAM-based Neuromorphic Accelerator
Kwunhang Wong, Songqi Wang, Wei Huang +8
Biologically plausible Spiking Neural Networks (SNNs), characterized by spike sparsity, are growing tremendous attention over intellectual edge devices and critical bio-medical app…
Older and Wiser: The Marriage of Device Aging and Intellectual Property Protection of Deep Neural Networks
Ning Lin, Shaocong Wang, Yue Zhang +6
Deep neural networks (DNNs), such as the widely-used GPT-3 with billions of parameters, are often kept secret due to high training costs and privacy concerns surrounding the data u…