A Scalable Mixture Model Based Defense Against Data Poisoning Attacks on Classifiers. - Xi Li 015; David J. Miller 001; Zhen Xiang; George Kesidis (DDDAS, 2020)

A Backdoor Attack against 3D Point Cloud Classifiers. - Zhen Xiang; David J. Miller 001; Siheng Chen; Xi Li 015; George Kesidis (ICCV, 2021)

Robust and Active Learning for Deep Neural Network Regression. - Xi Li 015; George Kesidis; David J. Miller 001; Maxime Bergeron; Ryan Ferguson; Vladimir Lucic (CoRR, 2021)

Backdoor Attack and Defense for Deep Regression. - Xi Li 015; George Kesidis; David J. Miller 001; Vladimir Lucic (CoRR, 2021)

Test-Time Detection of Backdoor Triggers for Poisoned Deep Neural Networks. - Xi Li 015; Zhen Xiang; David J. Miller 001; George Kesidis (ICASSP, 2022)

Detecting Backdoor Attacks against Point Cloud Classifiers. - Zhen Xiang; David J. Miller 001; Siheng Chen; Xi Li 015; George Kesidis (ICASSP, 2022)

A BIC-Based Mixture Model Defense Against Data Poisoning Attacks on Classifiers. - Xi Li 015; David J. Miller 001; Zhen Xiang; George Kesidis (MLSP, 2023)

Backdoor Mitigation by Correcting the Distribution of Neural Activations. - Xi Li 015; Zhen Xiang; David J. Miller 001; George Kesidis (CoRR, 2023)

Temporal-Distributed Backdoor Attack against Video Based Action Recognition. - Xi Li 015; Songhe Wang; Ruiquan Huang; Mahanth Gowda; George Kesidis (AAAI, 2024)

Universal Post-Training Reverse-Engineering Defense Against Backdoors in Deep Neural Networks. - Xi Li 015; Hang Wang; David J. Miller 001; George Kesidis (CoRR, 2024)

BIC-Based Mixture Model Defense Against Data Poisoning Attacks on Classifiers: A Comprehensive Study. - Xi Li 015; David J. Miller 001; Zhen Xiang; George Kesidis (IEEE Trans. Knowl. Data Eng., 2024)

Correcting the distribution of batch normalization signals for Trojan mitigation. - Xi Li 015; Zhen Xiang; David J. Miller 001; George Kesidis (Neurocomputing, 2025)