The full list of publications can be found on Google Scholar.

2022

Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models
Jialuo Chen, Jingyi Wang, Tinglan Peng, Youcheng Sun, Peng Cheng, Shouling Ji, Xingjun Ma, Bo Li, Dawn Song
IEEE Symposium on Security and Privacy (Oakland), 2022.

2021

Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks [Code]
Hanxun Huang, Yisen Wang, Sarah M. Erfani, Quanquan Gu, James Bailey, Xingjun Ma
Advances in Neural Information Processing Systems (NeurIPS), 2021.

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression [Code]
Jiabo He, Sarah M. Erfani, Xingjun Ma, James Bailey, Ying Chi, Xian-Sheng Hua
Advances in Neural Information Processing Systems (NeurIPS), 2021.

Anti-Backdoor Learning: Training Clean Models on Poisoned Data [Code]
Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma
Advances in Neural Information Processing Systems (NeurIPS), 2021.

Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning [Code]
Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan-Sheng Foo, Kian H. Low
Advances in Neural Information Processing Systems (NeurIPS), 2021.

Unlearnable Examples: Making Personal Data Unexploitable [Code] [Webpage]
Hanxun Huang, Xingjun Ma, Sarah M. Erfani, James Bailey, Yisen Wang
International Conference on Learning Representations (ICLR), 2021. (Spotlight, top 4%)
Press: MIT Technology Review, PURSUIT, Gadgets 360

Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks [Code]
Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma
International Conference on Learning Representations (ICLR), 2021.

Improving Adversarial Robustness via Channel-wise Activation Suppressing [Code]
Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Xingjun Ma, Yisen Wang
International Conference on Learning Representations (ICLR), 2021. (Spotlight, top 4%)

Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better [Code]
Bojia Zi*, Shihao Zhao*, Xingjun Ma, Yu-Gang Jiang
International Conference on Computer Vision (ICCV), 2021.

Noise Doesn’t Lie: Towards Universal Detection of Deep Inpainting
Ang Li, Qiuhong Ke, Xingjun Ma, Haiqin Weng, Zhiyuan Zong, Feng Xue, Rui Zhang
International Joint Conference on Artificial Intelligence (IJCAI), 2021.

Relationships between Local Intrinsic Dimensionality and Tail Entropy [Video]
James Bailey, Michael Houle, Xingjun Ma
International Conference on Similarity Search and Applications (SISAP), Dortmund, Germany, 2021. (Best Paper Award)

RobOT: Robustness-Oriented Testing for Deep Learning Systems [Tookit]
Jingyi Wang, Jialuo Chen, Youcheng Sun, Xingjun Ma, Dongxia Wang, Jun Sun, Peng Cheng
International Conference on Software Engineering (ICSE), 2021.

Sub-trajectory Similarity Join with Obfuscation
Yanchuan Chang, Jianzhong Qi, Egemen Tanin, Xingjun Ma, Hanan Samet
International Conference on Scientific and Statistical Database Management (SSDBM), 2021. (Best Paper Runner-up Award)

SpineOne: A One-Stage Detection Framework for Degenerative Discs and Vertebrae
Jiabo He, Wei Liu, Yu Wang, Xingjun Ma, Xian-Sheng Hua
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2021.

Dual Head Adversarial Training [Code]
Yujing Jiang, Xingjun Ma, Sarah M. Erfani, James Bailey
International Joint Conference on Neural Networks (IJCNN), 2021.

Neural Architecture Search via Combinatorial Multi-Armed Bandit
Hanxun Huang, Xingjun Ma, Sarah M. Erfani, James Bailey
International Joint Conference on Neural Networks (IJCNN), 2021.

Federated Learning with Extreme Label Skew: A Data Extension Approach
Saheed Tijani, Xingjun Ma, Frank Jiang, Robin Doss
International Joint Conference on Neural Networks (IJCNN), 2021.

Microwave Link Failures Prediction via LSTM-based Feature Fusion Network
Zichan Ruan, Shuiqiao Yang, Lei Pan, Xingjun Ma, Wei Luo, Marthie Grobler
International Joint Conference on Neural Networks (IJCNN), 2021.

Anomaly Detection for Scenario-based Insider Activities using CGAN Augmented Data
R G Gayathri, Atul Sajjanhar, Yong Xiang, Xingjun Ma
International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2021.

ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks
Khondker Fariha Hossain, Sharif Amit Kamran, Alireza Tavakkoli, Lei Pan, Xingjun Ma, Sutharshan Rajasegarar, Chandan Karmaker
International Conference on Machine Learning and Applications (ICMLA), 2021.

Exploring the Vulnerability of Natural Language Processing Models via Universal Adversarial Texts
Xinzhe Li, Ming Liu, Xingjun Ma, Longxiang Gao
Australasian Language Technology Association Workshop (ALTA), 2021.

Surgical approach to the facial recess influences the acceptable trajectory of cochlear implantation electrodes
Bridget Copson, Sudanthi Wijewickrema, Xingjun Ma, Yun Zhou, Jean-Marc Gerard, Stephen O’Leary
European Archives of Oto-Rhino-Laryngology, 1-11, 2021.

What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space [Code]
Shihao Zhao, Xingjun Ma, Yisen Wang, James Bailey, Bo Li, Yu-Gang Jiang
arXiv preprint.

Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness
Xingjun Ma*, Linxi Jiang*, Hanxun Huang, Zejia Weng, James Bailey, Yu-Gang Jiang
arXiv preprint.

A Lazy Approach for Efficient Index Learning
Guanli Liu, Lars Kulik, Xingjun Ma, Jianzhong Qi
arXiv preprint.

Adversarial Interaction Attack: Fooling AI to Misinterpret Human Intentions
Nodens Koren, Qiuhong Ke, Yisen Wang, James Bailey, Xingjun Ma
arXiv preprint.

2020

Normalized Loss Functions for Deep Learning with Noisy Labels [Code]
Xingjun Ma*, Hanxun Huang*, Yisen Wang, Simone Romano, Sarah M. Erfani, James Bailey
International Conference on Machine Learning (ICML), 2020.

Improving Adversarial Robustness Requires Revisiting Misclassified Examples [Code]
Yisen Wang, Difan Zou, Jinfeng Yi, James Bailey, Xingjun Ma, Quanquan Gu
International Conference on Learning Representations (ICLR), 2020.

Skip Connections Matter: on the Transferability of Adversarial Examples Generated with ResNets [Code]
Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma
International Conference on Learning Representations (ICLR), 2020. (Spotlight, top 4%)

Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems
Xingjun Ma*, Yuhao Niu*, Lin Gu, Yisen Wang, Yitian Zhao, James Bailey, Feng Lu
Pattern Recognition (PR), 110, 2021, 107332. (accepted in 2020)
Press: Computer Vision News

Clean-Label Backdoor Attacks on Video Recognition Models [Code]
Shihao Zhao, Xingjun Ma, Xiang Zheng, James Bailey, Jingjing Chen, Yu-Gang Jiang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles [Code]
Ranjie Duan, Xingjun Ma, Yisen Wang, James Bailey, Kai Qin, Yun Yang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection [Dataset/Code]
Bojia Zi, Jingjing Chen, Minghao Chang, Xingjun Ma, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), 2020.

Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks [Code]
Yunfei Liu, Xingjun Ma, James Bailey, Feng Lu
European Conference on Computer Vision (ECCV), 2020.

Short-Term and Long-Term Context Aggregation Network for Video Inpainting
Ang Li, Shanshan Zhao, Xingjun Ma, Mingming Gong, Jianzhong Qi, Rui Zhang, Dacheng Tao, Ramamohanarao Kotagiri
European Conference on Computer Vision (ECCV), 2020. (Spotlight, top 5%)

Transfer of Automated Performance Feedback Models to Different Specimens in Virtual Reality Temporal Bone Surgery
Jesslyn Lamtara, Nathan Hanegbi, Benjamin Talks, Sudanthi Wijewickrema, Xingjun Ma, Patorn Piromchai, James Bailey and Stephen O’Leary
International Conference on Artificial Intelligence in Education (AIED), 2020.

Towards Fair and Privacy-Preserving Federated Deep Models [Code] [Medium] [Youtube]
Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin, Han Yu, and Kee Siong Ng
IEEE Transactions on Parallel and Distributed Systems (TPDS). (accepted in 2020)

How to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning
Lingjuan Lyu, Yitong Li, Karthik, Nandakumar, Jiangshan Yu, Xingjun Ma
IEEE Transactions on Dependable and Secure Computing (TDSC). (accepted in 2020)

Privacy and Robustness in Federated Learning: Attacks and Defenses
Lingjuan Lyu, Han Yu, Xingjun Ma, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu
arXiv preprint.

2019

On the Convergence and Robustness of Adversarial Training [Code]
Yisen Wang*, Xingjun Ma*, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu
International Conference on Machine Learning (ICML), Long Beach, USA, 2019. (Long talk, top 3%)

Symmetric Cross Entropy for Robust Learning with Noisy Labels [Code]
Yisen Wang*, Xingjun Ma*, Zaiyi Chen, Yuan Luo, Jinfeng Yi, James Bailey
International Conference on Computer Vision (ICCV), Seoul, Korea, 2019.

Black-box Adversarial Attacks on Video Recognition Models [Code]
Linxi Jiang*, Xingjun Ma*, Shaoxiang Chen, James Bailey, Yu-Gang Jiang
ACM International Conference on Multimedia (ACM MM), Nice, France, 2019.

Generative Image Inpainting with Submanifold Alignment
Ang Li, Jianzhong Qi, Rui Zhang, Xingjun Ma, Ramamohanarao Kotagiri
International Joint Conference on Artificial Intelligence (IJCAI), Macao, China, 2019.

Exploiting Patterns to Explain Individual Predictions
Yunzhe Jia, James Bailey, Ramamohanarao Kotagiri, Christopher Leckie, Xingjun Ma
Knowledge and Information Systems (KAIS). (accepted in 2019)

Quality Evaluation of GANs Using Cross Local Intrinsic Dimensionality [Paper]
Sukarna Barua, Xingjun Ma, Sarah M. Erfani, Michael E. Houle, James Bailey
arxiv preprint.

2018

Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality [Code]
Xingjun Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi Wijewickrema, Grant Schoenebeck, Dawn Song, Michael E. Houle, James Bailey
International Conference on Learning Representations (ICLR), Vancouver, BC, Canada, 2018, (Oral, top 2%)

Dimensionality-Driven Learning with Noisy Labels [Code]
Xingjun Ma*, Yisen Wang*, Michael E. Houle, Shuo Zhou, Sarah M. Erfani, Shu-Tao Xia, Sudanthi Wijewickrema, James Bailey
International Conference on Machine Learning (ICML), Stockholm, Sweden, 2018. (Long talk, top 4%)

Iterative Learning with Open-set Noisy Labels
Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, USA, 2018. (Spotlight, top 6%)

Providing Automated Real-Time Technical Feedback for Virtual Reality Based Surgical Training: Is the Simpler the Better?
Sudanthi Wijewickrema, Xingjun Ma, Patorn Piromchai, Robert Briggs, James Bailey, Gregor Kennedy, Stephen O’Leary
International Conference on Artificial Intelligence in Education (AIED), London, UK, 2018

Development and Validation of a Virtual Reality Tutor to Teach Clinically Oriented Surgical Anatomy of the Ear
Sudanthi Wijewickrema, Bridget Copson, Xingjun Ma, Robert Briggs, James Bailey, Gregor Kennedy and Stephen O’Leary
IEEE International Symposium on Computer-Based Medical Systems (CBMS), 2018

2017

Adversarial Generation of Real-time Feedback with Neural Networks for Simulation-based Training
Xingjun Ma, Sudanthi Wijewickrema, Shuo Zhou, Yun Zhou, Zakaria Mhammedi, Stephen O’Leary, James Bailey.
International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, 2017. (Oral)

Unbiased Multivariate Correlation Analysis
Yisen Wang, Simone Romano, Nguyen Xuan Vinh, James Bailey, Xingjun Ma, Shu-Tao Xia
AAAI Conference on Artificial Intelligence (AAAI), San Francisco, USA, 2017. (Oral)

Providing Effective Real-time Feedback in Simulation-based Surgical Training
Xingjun Ma, Sudanthi Wijewickrema, Yun Zhou, Shuo Zhou, Stephen O’Leary, James Bailey
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Quebec City, Canada, 2017.

Simulation for Training Cochlear Implant Electrode Insertion
Xingjun Ma, Sudanthi Wijewickremay, Yun Zhou, Bridget Copson, James Bailey, Gregor Kennedy, Stephen O’Leary
IEEE International Symposium on Computer-Based Medical Systems (CBMS), Thessaloniki, Greece, 2017

Design and Evaluation of a Virtual Reality Simulation Module for Training Advanced Temporal Bone Surgery
Sudanthi Wijewickremay, Bridget Copson, Yun Zhou, Xingjun Ma, Robert Briggs, James Bailey, Gregor Kennedy, Stephen O’Leary
IEEE International Symposium on Computer-Based Medical Systems (CBMS), Thessaloniki, Greece, 2017

Feedback Techniques in Computer-Based Simulation Training: A Survey
Sudanthi Wijewickrema, Xingjun Ma, James Bailey, Gregor Kennedy and Stephen O’Leary
arXiv preprint.

2016

Finding Influentials in Twitter: A Temporal Influence Ranking Model [Paper]
Xingjun Ma, Chunping Li, James Bailey, Sudanthi Wijewickrema
The Australasian Data Mining Conference (AusDM), Canberra, Australia, 2016