94 citations · 237 across the 12 of their papers we have counts for
12 papers
NOTABLE: Transferable Backdoor Attacks Against Prompt-based NLP Models
Kai Mei, Zheng Li, Zhenting Wang +2
Prompt-based learning is vulnerable to backdoor attacks. Existing backdoor attacks against prompt-based models consider injecting backdoors into the entire embedding layers or word…
UNICORN: A Unified Backdoor Trigger Inversion Framework
Zhenting Wang, Kai Mei, Juan Zhai +1
The backdoor attack, where the adversary uses inputs stamped with triggers (e.g., a patch) to activate pre-planted malicious behaviors, is a severe threat to Deep Neural Network (D…
Rethinking the Reverse-engineering of Trojan Triggers
Zhenting Wang, Kai Mei, Hailun Ding +2
Deep Neural Networks are vulnerable to Trojan (or backdoor) attacks. Reverse-engineering methods can reconstruct the trigger and thus identify affected models. Existing reverse-eng…
Theoretical Analysis of Deep Neural Networks in Physical Layer Communication
Jun Liu, Haitao Zhao, Dongtang Ma +2
Recently, deep neural network (DNN)-based physical layer communication techniques have attracted considerable interest. Although their potential to enhance communication systems an…
A Low Complexity Learning-based Channel Estimation for OFDM Systems with Online Training
Kai Mei, Jun Liu, Xiaoying Zhang +3
In this paper, we devise a highly efficient machine learning-based channel estimation for orthogonal frequency division multiplexing (OFDM) systems, in which the training of the es…
Opening the Black Box of Deep Neural Networks in Physical Layer Communication
Jun Liu, Haitao Zhao, Dongtang Ma +2
Deep Neural Network (DNN)-based physical layer techniques are attracting considerable interest due to their potential to enhance communication systems. However, most studies in the…
Fine Timing and Frequency Synchronization for MIMO-OFDM: An Extreme Learning Approach
Jun Liu, Kai Mei, Xiaochen Zhang +4
Multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) is a key technology component in the evolution towards cognitive radio (CR) in next-generation…
6G White Paper on Machine Learning in Wireless Communication Networks
Samad Ali, Walid Saad, Nandana Rajatheva +24
The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of socie…
Enhanced LMMSE Estimation Capable of Selecting Parameters
Kai Mei, Jun Liu, Xiaoran Liu +3
In the linear minimum mean square error (LMMSE) estimation for orthogonal frequency division multiplexing (OFDM) systems, the problem about the determination of the algorithm's par…
Performance Analysis on Machine Learning-Based Channel Estimation
Kai Mei, Jun Liu, Xiaochen Zhang +2
Recently, machine learning-based channel estimation has attracted much attention. The performance of machine learning-based estimation has been validated by simulation experiments.…
Deep Neural Network Aided Scenario Identification in Wireless Multi-path Fading Channels
Jun Liu, Kai Mei, Dongtang Ma +1
This letter illustrates our preliminary works in deep nerual network (DNN) for wireless communication scenario identification in wireless multi-path fading channels. In this letter…
High-precision timing and frequency synchronization method for MIMO-OFDM systems in double-selective channels
Jun Liu, Kai Mei, Xiaochen Zhang +3
In this letter, a novel synchronization method for MIMO-OFDM systems is proposed. The new approach has an accurate estimate of both symbol timing and large frequency offest. Simula…