211 citations · 1k across the 37 of their papers we have counts for
6 papers · 1 filter
Gaining the Sparse Rewards by Exploring Lottery Tickets in Spiking Neural Network
Hao Cheng, Jiahang Cao, Erjia Xiao +2
Deploying energy-efficient deep learning algorithms on computational-limited devices, such as robots, is still a pressing issue for real-world applications. Spiking Neural Networks…
A preconditioned MINRES method for block lower triangular Toeplitz systems
Congcong Li, Xuelei Lin, Sean Hon +1
In this study, a novel preconditioner based on the absolute-value block -circulant matrix approximation is developed, specifically designed for nonsymmetric dense block lower tr…
A block -circulant based preconditioned MINRES method for wave equations
Xue-lei Lin, Sean Hon
In this work, we propose an absolute value block -circulant preconditioner for the minimal residual (MINRES) method to solve an all-at-once system arising from the discretizatio…
Can Adversarial Examples Be Parsed to Reveal Victim Model Information?
Yuguang Yao, Jiancheng Liu, Yifan Gong +4
Numerous adversarial attack methods have been developed to generate imperceptible image perturbations that can cause erroneous predictions of state-of-the-art machine learning (ML)…
Less is More: Data Pruning for Faster Adversarial Training
Yize Li, Pu Zhao, Xue Lin +2
Deep neural networks (DNNs) are sensitive to adversarial examples, resulting in fragile and unreliable performance in the real world. Although adversarial training (AT) is currentl…
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms
Minzhou Pan, Yi Zeng, Lingjuan Lyu +2
Backdoor data detection is traditionally studied in an end-to-end supervised learning (SL) setting. However, recent years have seen the proliferating adoption of self-supervised le…