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2020 – today
- 2024
[j10]Xingjun Ma, Linxi Jiang, Hanxun Huang
, Zejia Weng, James Bailey, Yu-Gang Jiang:
Imbalanced gradients: a subtle cause of overestimated adversarial robustness. Mach. Learn. 113(5): 2301-2326 (2024)- [j9]Lingjuan Lyu, Han Yu, Xingjun Ma, Chen Chen, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu:
Privacy and Robustness in Federated Learning: Attacks and Defenses. IEEE Trans. Neural Networks Learn. Syst. 35(7): 8726-8746 (2024) - [c65]Xiang Zheng, Xingjun Ma, Shengjie Wang, Xinyu Wang, Chao Shen, Cong Wang:
Toward Evaluating Robustness of Reinforcement Learning with Adversarial Policy. DSN 2024: 288-301 - [c64]Hanxun Huang, Ricardo J. G. B. Campello, Sarah Monazam Erfani, Xingjun Ma, Michael E. Houle, James Bailey:
LDReg: Local Dimensionality Regularized Self-Supervised Learning. ICLR 2024 - [c63]Xiang Zheng, Xingjun Ma, Chao Shen, Cong Wang:
Constrained Intrinsic Motivation for Reinforcement Learning. IJCAI 2024: 5608-5616 - [c62]Xin Wang, Kai Chen, Xingjun Ma, Zhineng Chen, Jingjing Chen, Yu-Gang Jiang:
AdvQDet: Detecting Query-Based Adversarial Attacks with Adversarial Contrastive Prompt Tuning. ACM Multimedia 2024: 6212-6221 - [c61]Tianyi Lu, Xing Zhang, Jiaxi Gu, Renjing Pei, Songcen Xu, Xingjun Ma, Hang Xu, Zuxuan Wu:
Fuse Your Latents: Video Editing with Multi-source Latent Diffusion Models. ACM Multimedia 2024: 6745-6754 - [c60]Ruofan Wang, Xingjun Ma, Hanxu Zhou, Chuanjun Ji, Guangnan Ye, Yu-Gang Jiang:
White-box Multimodal Jailbreaks Against Large Vision-Language Models. ACM Multimedia 2024: 6920-6928 - [c59]Yifeng Gao, Yuhua Sun, Xingjun Ma, Zuxuan Wu, Yu-Gang Jiang:
ModelLock: Locking Your Model With a Spell. ACM Multimedia 2024: 11156-11165 - [c58]Yixu Wang, Yan Teng, Kexin Huang, Chengqi Lyu, Songyang Zhang, Wenwei Zhang, Xingjun Ma, Yu-Gang Jiang, Yu Qiao, Yingchun Wang:
Fake Alignment: Are LLMs Really Aligned Well? NAACL-HLT 2024: 4696-4712 - [c57]Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani, James Bailey:
Unlearnable Examples for Time Series. PAKDD (6) 2024: 213-225 - [c56]Xueqi Ma, Xingjun Ma, Sarah M. Erfani, James Bailey:
Training Sparse Graph Neural Networks via Pruning and Sprouting. SDM 2024: 136-144 - [i78]Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani, Yige Li, James Bailey:
End-to-End Anti-Backdoor Learning on Images and Time Series. CoRR abs/2401.03215 (2024) - [i77]Hanxun Huang, Ricardo J. G. B. Campello, Sarah Monazam Erfani, Xingjun Ma, Michael E. Houle, James Bailey:
LDReg: Local Dimensionality Regularized Self-Supervised Learning. CoRR abs/2401.10474 (2024) - [i76]Yige Li, Xingjun Ma, Jiabo He, Hanxun Huang, Yu-Gang Jiang:
Multi-Trigger Backdoor Attacks: More Triggers, More Threats. CoRR abs/2401.15295 (2024) - [i75]Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani, James Bailey:
Unlearnable Examples For Time Series. CoRR abs/2402.02028 (2024) - [i74]Hengyuan Xu, Liyao Xiang, Xingjun Ma, Borui Yang, Baochun Li:
Hufu: A Modality-Agnositc Watermarking System for Pre-Trained Transformers via Permutation Equivariance. CoRR abs/2403.05842 (2024) - [i73]Pagnarasmey Pit, Xingjun Ma, Mike Conway, Qingyu Chen, James Bailey, Henry Pit, Putrasmey Keo, Watey Diep, Yu-Gang Jiang:
Whose Side Are You On? Investigating the Political Stance of Large Language Models. CoRR abs/2403.13840 (2024) - [i72]Xuran Li, Peng Wu, Yanting Chen, Xingjun Ma, Zhen Zhang, Kaixiang Dong:
The Double-Edged Sword of Input Perturbations to Robust Accurate Fairness. CoRR abs/2404.01356 (2024) - [i71]Kun Zhai, Yifeng Gao, Xingjun Ma, Difan Zou, Guangnan Ye, Yu-Gang Jiang:
The Dog Walking Theory: Rethinking Convergence in Federated Learning. CoRR abs/2404.11888 (2024) - [i70]Yang Bai, Ge Pei, Jindong Gu, Yong Yang, Xingjun Ma:
Special Characters Attack: Toward Scalable Training Data Extraction From Large Language Models. CoRR abs/2405.05990 (2024) - [i69]Liuzhi Zhou, Yu He, Kun Zhai, Xiang Liu, Sen Liu, Xingjun Ma, Guangnan Ye, Yu-Gang Jiang, Hongfeng Chai:
FedCAda: Adaptive Client-Side Optimization for Accelerated and Stable Federated Learning. CoRR abs/2405.11811 (2024) - [i68]Yifeng Gao, Yuhua Sun, Xingjun Ma, Zuxuan Wu, Yu-Gang Jiang:
ModelLock: Locking Your Model With a Spell. CoRR abs/2405.16285 (2024) - [i67]Ruofan Wang, Xingjun Ma, Hanxu Zhou, Chuanjun Ji, Guangnan Ye, Yu-Gang Jiang:
White-box Multimodal Jailbreaks Against Large Vision-Language Models. CoRR abs/2405.17894 (2024) - [i66]Xincheng Shuai, Henghui Ding, Xingjun Ma, Rongcheng Tu, Yu-Gang Jiang, Dacheng Tao:
A Survey of Multimodal-Guided Image Editing with Text-to-Image Diffusion Models. CoRR abs/2406.14555 (2024) - [i65]Ziming Zhao, Tiehua Zhang, Zhishu Shen, Hai Dong, Xingjun Ma, Xianhui Liu, Yun Yang:
CHASE: A Causal Heterogeneous Graph based Framework for Root Cause Analysis in Multimodal Microservice Systems. CoRR abs/2406.19711 (2024) - [i64]Xiang Zheng, Xingjun Ma, Chao Shen, Cong Wang:
Constrained Intrinsic Motivation for Reinforcement Learning. CoRR abs/2407.09247 (2024) - [i63]Weijie Zheng, Xingjun Ma, Hanxun Huang, Zuxuan Wu, Yu-Gang Jiang:
Downstream Transfer Attack: Adversarial Attacks on Downstream Models with Pre-trained Vision Transformers. CoRR abs/2408.01705 (2024) - [i62]Xin Wang, Kai Chen, Xingjun Ma, Zhineng Chen, Jingjing Chen, Yu-Gang Jiang:
AdvQDet: Detecting Query-Based Adversarial Attacks with Adversarial Contrastive Prompt Tuning. CoRR abs/2408.01978 (2024) - [i61]Jiahao Zhang, Zilong Wang, Ruofan Wang, Xingjun Ma, Yu-Gang Jiang:
EnJa: Ensemble Jailbreak on Large Language Models. CoRR abs/2408.03603 (2024) - [i60]Yige Li, Hanxun Huang, Yunhan Zhao, Xingjun Ma, Jun Sun:
BackdoorLLM: A Comprehensive Benchmark for Backdoor Attacks on Large Language Models. CoRR abs/2408.12798 (2024) - [i59]Yunhao Chen, Xingjun Ma, Difan Zou, Yu-Gang Jiang:
Towards a Theoretical Understanding of Memorization in Diffusion Models. CoRR abs/2410.02467 (2024) - 2023
- [j8]James Bailey, Michael E. Houle, Xingjun Ma:
Relationships between tail entropies and local intrinsic dimensionality and their use for estimation and feature representation. Inf. Syst. 118: 102245 (2023) - [j7]Chuxuan Tong, Xi Zheng, Jianhua Li, Xingjun Ma, Longxiang Gao, Yong Xiang:
Query-Efficient Black-Box Adversarial Attacks on Automatic Speech Recognition. IEEE ACM Trans. Audio Speech Lang. Process. 31: 3981-3992 (2023) - [j6]Jialuo Chen, Jingyi Wang, Xingjun Ma, Youcheng Sun, Jun Sun, Peixin Zhang, Peng Cheng:
QuoTe: Quality-oriented Testing for Deep Learning Systems. ACM Trans. Softw. Eng. Methodol. 32(5): 125:1-125:33 (2023) - [c55]Jiaming Zhang, Xingjun Ma, Qi Yi, Jitao Sang, Yu-Gang Jiang, Yaowei Wang, Changsheng Xu:
Unlearnable Clusters: Towards Label-Agnostic Unlearnable Examples. CVPR 2023: 3984-3993 - [c54]Hanxun Huang, Xingjun Ma, Sarah Monazam Erfani, James Bailey:
Distilling Cognitive Backdoor Patterns within an Image. ICLR 2023 - [c53]Jie Ren, Han Xu, Yuxuan Wan, Xingjun Ma, Lichao Sun, Jiliang Tang:
Transferable Unlearnable Examples. ICLR 2023 - [c52]Yige Li, Xixiang Lyu, Xingjun Ma, Nodens Koren, Lingjuan Lyu, Bo Li, Yu-Gang Jiang:
Reconstructive Neuron Pruning for Backdoor Defense. ICML 2023: 19837-19854 - [c51]Jialuo Chen, Youcheng Sun, Jingyi Wang, Peng Cheng, Xingjun Ma:
DEEPJUDGE: A Testing Framework for Copyright Protection of Deep Learning Models. ICSE Companion 2023: 64-67 - [c50]Yilun Zhang, Yuqian Fu, Xingjun Ma, Lizhe Qi, Jingjing Chen, Zuxuan Wu, Yu-Gang Jiang:
On the Importance of Spatial Relations for Few-shot Action Recognition. ACM Multimedia 2023: 2243-2251 - [c49]Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani, James Bailey:
Backdoor Attacks on Time Series: A Generative Approach. SaTML 2023: 392-403 - [i58]Jiaming Zhang, Xingjun Ma, Qi Yi, Jitao Sang, Yugang Jiang, Yaowei Wang, Changsheng Xu:
Unlearnable Clusters: Towards Label-agnostic Unlearnable Examples. CoRR abs/2301.01217 (2023) - [i57]Hanxun Huang, Xingjun Ma, Sarah M. Erfani, James Bailey:
Distilling Cognitive Backdoor Patterns within an Image. CoRR abs/2301.10908 (2023) - [i56]Xiang Zheng, Xingjun Ma, Shengjie Wang, Xinyu Wang, Chao Shen, Cong Wang:
IMAP: Intrinsically Motivated Adversarial Policy. CoRR abs/2305.02605 (2023) - [i55]Yige Li, Xixiang Lyu, Xingjun Ma, Nodens Koren, Lingjuan Lyu, Bo Li, Yu-Gang Jiang:
Reconstructive Neuron Pruning for Backdoor Defense. CoRR abs/2305.14876 (2023) - [i54]Tiehua Zhang, Yuze Liu, Zhishu Shen, Xingjun Ma, Xin Chen, Xiaowei Huang, Jun Yin, Jiong Jin:
Learning from Heterogeneity: A Dynamic Learning Framework for Hypergraphs. CoRR abs/2307.03411 (2023) - [i53]Yilun Zhang, Yuqian Fu, Xingjun Ma, Lizhe Qi, Jingjing Chen, Zuxuan Wu, Yu-Gang Jiang:
On the Importance of Spatial Relations for Few-shot Action Recognition. CoRR abs/2308.07119 (2023) - [i52]Yixu Wang, Yan Teng, Kexin Huang, Chengqi Lyu, Songyang Zhang, Wenwei Zhang, Xingjun Ma, Yu-Gang Jiang, Yu Qiao, Yingchun Wang:
Fake Alignment: Are LLMs Really Aligned Well? CoRR abs/2311.05915 (2023) - [i51]Jiaming Zhang, Xingjun Ma, Xin Wang, Lingyu Qiu, Jiaqi Wang, Yu-Gang Jiang, Jitao Sang:
Adversarial Prompt Tuning for Vision-Language Models. CoRR abs/2311.11261 (2023) - 2022
- [j5]James Bailey, Michael E. Houle, Xingjun Ma:
Local Intrinsic Dimensionality, Entropy and Statistical Divergences. Entropy 24(9): 1220 (2022) - [j4]Lingjuan Lyu, Yitong Li, Karthik Nandakumar, Jiangshan Yu, Xingjun Ma:
How to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning. IEEE Trans. Dependable Secur. Comput. 19(2): 1003-1017 (2022) - [c48]Zhiyuan Zhang, Lingjuan Lyu, Xingjun Ma, Chenguang Wang, Xu Sun:
Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models. EMNLP (Findings) 2022: 355-372 - [c47]Yiming Li, Haoxiang Zhong, Xingjun Ma, Yong Jiang, Shu-Tao Xia:
Few-Shot Backdoor Attacks on Visual Object Tracking. ICLR 2022 - [c46]Khondker Fariha Hossain, Sharif Amit Kamran, Alireza Tavakkoli, Xingjun Ma:
ECG-ATK-GAN: Robustness Against Adversarial Attacks on ECGs Using Conditional Generative Adversarial Networks. AMAI@MICCAI 2022: 68-78 - [c45]Yuhua Sun, Tailai Zhang, Xingjun Ma, Pan Zhou, Jian Lou, Zichuan Xu, Xing Di, Yu Cheng, Lichao Sun:
Backdoor Attacks on Crowd Counting. ACM Multimedia 2022: 5351-5360 - [c44]Chen Chen, Yuchen Liu, Xingjun Ma, Lingjuan Lyu:
CalFAT: Calibrated Federated Adversarial Training with Label Skewness. NeurIPS 2022 - [c43]Jialuo Chen, Jingyi Wang, Tinglan Peng, Youcheng Sun, Peng Cheng, Shouling Ji, Xingjun Ma, Bo Li, Dawn Song:
Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models. SP 2022: 824-841 - [i50]Yiming Li, Haoxiang Zhong, Xingjun Ma, Yong Jiang, Shu-Tao Xia:
Few-Shot Backdoor Attacks on Visual Object Tracking. CoRR abs/2201.13178 (2022) - [i49]Xiangshan Gao, Xingjun Ma, Jingyi Wang, Youcheng Sun, Bo Li, Shouling Ji, Peng Cheng, Jiming Chen:
VeriFi: Towards Verifiable Federated Unlearning. CoRR abs/2205.12709 (2022) - [i48]Chen Chen, Yuchen Liu, Xingjun Ma, Lingjuan Lyu:
CalFAT: Calibrated Federated Adversarial Training with Label Skewness. CoRR abs/2205.14926 (2022) - [i47]Yuhua Sun, Tailai Zhang, Xingjun Ma, Pan Zhou, Jian Lou, Zichuan Xu, Xing Di, Yu Cheng, Lichao Sun:
Backdoor Attacks on Crowd Counting. CoRR abs/2207.05641 (2022) - [i46]Zhiyuan Zhang, Lingjuan Lyu, Xingjun Ma, Chenguang Wang, Xu Sun:
Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models. CoRR abs/2210.09545 (2022) - [i45]Jie Ren, Han Xu, Yuxuan Wan, Xingjun Ma, Lichao Sun, Jiliang Tang:
Transferable Unlearnable Examples. CoRR abs/2210.10114 (2022) - [i44]Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani, James Bailey:
Backdoor Attacks on Time Series: A Generative Approach. CoRR abs/2211.07915 (2022) - 2021
- [j3]Xingjun Ma, Yuhao Niu, Lin Gu, Yisen Wang, Yitian Zhao, James Bailey, Feng Lu:
Understanding adversarial attacks on deep learning based medical image analysis systems. Pattern Recognit. 110: 107332 (2021) - [c42]Jiabo He, Wei Liu, Yu Wang, Xingjun Ma, Xian-Sheng Hua:
SpineOne: A One-Stage Detection Framework for Degenerative Discs and Vertebrae. BIBM 2021: 1331-1334 - [c41]Bojia Zi, Shihao Zhao, Xingjun Ma, Yu-Gang Jiang:
Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better. ICCV 2021: 16423-16432 - [c40]Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Xingjun Ma, Yisen Wang:
Improving Adversarial Robustness via Channel-wise Activation Suppressing. ICLR 2021 - [c39]Hanxun Huang, Xingjun Ma, Sarah Monazam Erfani, James Bailey, Yisen Wang:
Unlearnable Examples: Making Personal Data Unexploitable. ICLR 2021 - [c38]Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma:
Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks. ICLR 2021 - [c37]Khondker Fariha Hossain, Sharif Amit Kamran, Alireza Tavakkoli, Lei Pan, Xingjun Ma, Sutharshan Rajasegarar, Chandan Karmaker:
ECG-Adv-GAN: Detecting ECG Adversarial Examples with Conditional Generative Adversarial Networks. ICMLA 2021: 50-56 - [c36]Jingyi Wang, Jialuo Chen, Youcheng Sun, Xingjun Ma, Dongxia Wang, Jun Sun, Peng Cheng:
RobOT: Robustness-Oriented Testing for Deep Learning Systems. ICSE 2021: 300-311 - [c35]Ang Li, Qiuhong Ke, Xingjun Ma, Haiqin Weng, Zhiyuan Zong, Feng Xue, Rui Zhang:
Noise Doesn't Lie: Towards Universal Detection of Deep Inpainting. IJCAI 2021: 786-792 - [c34]Hanxun Huang, Xingjun Ma, Sarah M. Erfani, James Bailey:
Neural Architecture Search via Combinatorial Multi-Armed Bandit. IJCNN 2021: 1-8 - [c33]Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani, James Bailey:
Dual Head Adversarial Training. IJCNN 2021: 1-8 - [c32]Zichan Ruan, Shuiqiao Yang, Lei Pan, Xingjun Ma, Wei Luo, Marthie Grobler:
Microwave Link Failures Prediction via LSTM-based Feature Fusion Network. IJCNN 2021: 1-8 - [c31]Saheed A. Tijani, Xingjun Ma, Ran Zhang, Frank Jiang, Robin Doss:
Federated Learning with Extreme Label Skew: A Data Extension Approach. IJCNN 2021: 1-8 - [c30]Hanxun Huang, Yisen Wang, Sarah M. Erfani, Quanquan Gu, James Bailey, Xingjun Ma:
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks. NeurIPS 2021: 5545-5559 - [c29]Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma:
Anti-Backdoor Learning: Training Clean Models on Poisoned Data. NeurIPS 2021: 14900-14912 - [c28]Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo, Bryan Kian Hsiang Low:
Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning. NeurIPS 2021: 16104-16117 - [c27]Jiabo He, Sarah M. Erfani, Xingjun Ma, James Bailey, Ying Chi, Xian-Sheng Hua:
$\alpha$-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression. NeurIPS 2021: 20230-20242 - [c26]James Bailey, Michael E. Houle, Xingjun Ma:
Relationships Between Local Intrinsic Dimensionality and Tail Entropy. SISAP 2021: 186-200 - [c25]Yanchuan Chang, Jianzhong Qi, Egemen Tanin, Xingjun Ma, Hanan Samet:
Sub-trajectory Similarity Join with Obfuscation. SSDBM 2021: 181-192 - [c24]R. G. Gayathri, Atul Sajjanhar, Yong Xiang, Xingjun Ma:
Anomaly Detection for Scenario-based Insider Activities using CGAN Augmented Data. TrustCom 2021: 718-725 - [i43]Hanxun Huang, Xingjun Ma, Sarah M. Erfani, James Bailey:
Neural Architecture Search via Combinatorial Multi-Armed Bandit. CoRR abs/2101.00336 (2021) - [i42]Bojia Zi, Minghao Chang, Jingjing Chen, Xingjun Ma, Yu-Gang Jiang:
WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection. CoRR abs/2101.01456 (2021) - [i41]Hanxun Huang, Xingjun Ma, Sarah Monazam Erfani, James Bailey, Yisen Wang:
Unlearnable Examples: Making Personal Data Unexploitable. CoRR abs/2101.04898 (2021) - [i40]Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma:
Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks. CoRR abs/2101.05930 (2021) - [i39]Nodens Koren, Qiuhong Ke, Yisen Wang, James Bailey, Xingjun Ma:
Adversarial Interaction Attack: Fooling AI to Misinterpret Human Intentions. CoRR abs/2101.06704 (2021) - [i38]Shihao Zhao, Xingjun Ma, Yisen Wang, James Bailey, Bo Li, Yu-Gang Jiang:
What Do Deep Nets Learn? Class-wise Patterns Revealed in the Input Space. CoRR abs/2101.06898 (2021) - [i37]Jingyi Wang, Jialuo Chen, Youcheng Sun, Xingjun Ma, Dongxia Wang, Jun Sun, Peng Cheng:
RobOT: Robustness-Oriented Testing for Deep Learning Systems. CoRR abs/2102.05913 (2021) - [i36]R. G. Gayathri, Atul Sajjanhar, Yong Xiang, Xingjun Ma:
Multi-class Classification Based Anomaly Detection of Insider Activities. CoRR abs/2102.07277 (2021) - [i35]Guanli Liu, Lars Kulik, Xingjun Ma, Jianzhong Qi:
A Lazy Approach for Efficient Index Learning. CoRR abs/2102.08081 (2021) - [i34]Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Xingjun Ma, Yisen Wang:
Improving Adversarial Robustness via Channel-wise Activation Suppressing. CoRR abs/2103.08307 (2021) - [i33]Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani, James Bailey:
Dual Head Adversarial Training. CoRR abs/2104.10377 (2021) - [i32]Ang Li, Qiuhong Ke, Xingjun Ma, Haiqin Weng, Zhiyuan Zong, Feng Xue, Rui Zhang:
Noise Doesn't Lie: Towards Universal Detection of Deep Inpainting. CoRR abs/2106.01532 (2021) - [i31]Yanchuan Chang, Jianzhong Qi, Egemen Tanin, Xingjun Ma, Hanan Samet:
Sub-trajectory Similarity Join with Obfuscation. CoRR abs/2106.03355 (2021) - [i30]Bojia Zi, Shihao Zhao, Xingjun Ma, Yu-Gang Jiang:
Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better. CoRR abs/2108.07969 (2021) - [i29]Hanxun Huang, Yisen Wang, Sarah Monazam Erfani, Quanquan Gu, James Bailey, Xingjun Ma:
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks. CoRR abs/2110.03825 (2021) - [i28]Khondker Fariha Hossain, Sharif Amit Kamran, Xingjun Ma, Alireza Tavakkoli:
ECG-ATK-GAN: Robustness against Adversarial Attacks on ECG using Conditional Generative Adversarial Networks. CoRR abs/2110.09983 (2021) - [i27]Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, Xingjun Ma:
Anti-Backdoor Learning: Training Clean Models on Poisoned Data. CoRR abs/2110.11571 (2021) - [i26]Jiabo He, Sarah M. Erfani, Xingjun Ma, James Bailey, Ying Chi, Xian-Sheng Hua:
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression. CoRR abs/2110.13675 (2021) - [i25]Jiabo He, Wei Liu, Yu Wang, Xingjun Ma, Xian-Sheng Hua:
SpineOne: A One-Stage Detection Framework for Degenerative Discs and Vertebrae. CoRR abs/2110.15082 (2021) - [i24]Jialuo Chen, Jingyi Wang, Tinglan Peng, Youcheng Sun, Peng Cheng, Shouling Ji, Xingjun Ma, Bo Li, Dawn Song:
Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models. CoRR abs/2112.05588 (2021) - [i23]Yisen Wang, Xingjun Ma, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu:
On the Convergence and Robustness of Adversarial Training. CoRR abs/2112.08304 (2021) - 2020
- [j2]Yunzhe Jia, James Bailey, Kotagiri Ramamohanarao, Christopher Leckie, Xingjun Ma:
Exploiting patterns to explain individual predictions. Knowl. Inf. Syst. 62(3): 927-950 (2020) - [j1]Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin, Han Yu, Kee Siong Ng:
Towards Fair and Privacy-Preserving Federated Deep Models. IEEE Trans. Parallel Distributed Syst. 31(11): 2524-2541 (2020) - [c23]Jesslyn Lamtara, Nathan Hanegbi, Benjamin Talks, Sudanthi N. R. Wijewickrema, Xingjun Ma, Patorn Piromchai, James Bailey, Stephen J. O'Leary:
Transfer of Automated Performance Feedback Models to Different Specimens in Virtual Reality Temporal Bone Surgery. AIED (1) 2020: 296-308 - [c22]Ranjie Duan, Xingjun Ma, Yisen Wang, James Bailey, A. Kai Qin, Yun Yang:
Adversarial Camouflage: Hiding Physical-World Attacks With Natural Styles. CVPR 2020: 997-1005 - [c21]Shihao Zhao, Xingjun Ma, Xiang Zheng, James Bailey, Jingjing Chen, Yu-Gang Jiang:
Clean-Label Backdoor Attacks on Video Recognition Models. CVPR 2020: 14431-14440 - [c20]Yunfei Liu, Xingjun Ma, James Bailey, Feng Lu:
Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks. ECCV (10) 2020: 182-199 - [c19]Ang Li, Shanshan Zhao, Xingjun Ma, Mingming Gong, Jianzhong Qi, Rui Zhang, Dacheng Tao, Ramamohanarao Kotagiri:
Short-Term and Long-Term Context Aggregation Network for Video Inpainting. ECCV (4) 2020: 728-743 - [c18]Yisen Wang, Difan Zou, Jinfeng Yi, James Bailey, Xingjun Ma, Quanquan Gu:
Improving Adversarial Robustness Requires Revisiting Misclassified Examples. ICLR 2020 - [c17]Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma:
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets. ICLR 2020 - [c16]Xingjun Ma, Hanxun Huang, Yisen Wang, Simone Romano, Sarah M. Erfani, James Bailey:
Normalized Loss Functions for Deep Learning with Noisy Labels. ICML 2020: 6543-6553 - [c15]Bojia Zi, Minghao Chang, Jingjing Chen, Xingjun Ma, Yu-Gang Jiang:
WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection. ACM Multimedia 2020: 2382-2390 - [i22]Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma:
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets. CoRR abs/2002.05990 (2020) - [i21]Shihao Zhao, Xingjun Ma, Xiang Zheng, James Bailey, Jingjing Chen, Yu-Gang Jiang:
Clean-Label Backdoor Attacks on Video Recognition Models. CoRR abs/2003.03030 (2020) - [i20]Ranjie Duan, Xingjun Ma, Yisen Wang, James Bailey, A. Kai Qin, Yun Yang:
Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles. CoRR abs/2003.08757 (2020) - [i19]Xingjun Ma, Hanxun Huang, Yisen Wang, Simone Romano, Sarah M. Erfani, James Bailey:
Normalized Loss Functions for Deep Learning with Noisy Labels. CoRR abs/2006.13554 (2020) - [i18]Linxi Jiang, Xingjun Ma, Zejia Weng, James Bailey, Yu-Gang Jiang:
Imbalanced Gradients: A New Cause of Overestimated Adversarial Robustness. CoRR abs/2006.13726 (2020) - [i17]Yunfei Liu, Xingjun Ma, James Bailey, Feng Lu:
Reflection Backdoor: A Natural Backdoor Attack on Deep Neural Networks. CoRR abs/2007.02343 (2020) - [i16]Lingjuan Lyu, Yitong Li, Karthik Nandakumar, Jiangshan Yu, Xingjun Ma:
How to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning. CoRR abs/2007.09370 (2020) - [i15]Ang Li, Shanshan Zhao, Xingjun Ma, Mingming Gong, Jianzhong Qi, Rui Zhang, Dacheng Tao, Ramamohanarao Kotagiri:
Short-Term and Long-Term Context Aggregation Network for Video Inpainting. CoRR abs/2009.05721 (2020) - [i14]Lingjuan Lyu, Han Yu, Xingjun Ma, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu:
Privacy and Robustness in Federated Learning: Attacks and Defenses. CoRR abs/2012.06337 (2020)
2010 – 2019
- 2019
- [c14]Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jinfeng Yi, James Bailey:
Symmetric Cross Entropy for Robust Learning With Noisy Labels. ICCV 2019: 322-330 - [c13]Yisen Wang, Xingjun Ma, James Bailey, Jinfeng Yi, Bowen Zhou, Quanquan Gu:
On the Convergence and Robustness of Adversarial Training. ICML 2019: 6586-6595 - [c12]Ang Li, Jianzhong Qi, Rui Zhang, Xingjun Ma, Kotagiri Ramamohanarao:
Generative Image Inpainting with Submanifold Alignment. IJCAI 2019: 811-817 - [c11]Linxi Jiang, Xingjun Ma, Shaoxiang Chen, James Bailey, Yu-Gang Jiang:
Black-box Adversarial Attacks on Video Recognition Models. ACM Multimedia 2019: 864-872 - [i13]Linxi Jiang, Xingjun Ma, Shaoxiang Chen, James Bailey, Yu-Gang Jiang:
Black-box Adversarial Attacks on Video Recognition Models. CoRR abs/1904.05181 (2019) - [i12]Sukarna Barua, Xingjun Ma, Sarah Monazam Erfani, Michael E. Houle, James Bailey:
Quality Evaluation of GANs Using Cross Local Intrinsic Dimensionality. CoRR abs/1905.00643 (2019) - [i11]Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin:
Towards Fair and Decentralized Privacy-Preserving Deep Learning with Blockchain. CoRR abs/1906.01167 (2019) - [i10]Xingjun Ma, Yuhao Niu, Lin Gu, Yisen Wang, Yitian Zhao, James Bailey, Feng Lu:
Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems. CoRR abs/1907.10456 (2019) - [i9]Ang Li, Jianzhong Qi, Rui Zhang, Xingjun Ma, Kotagiri Ramamohanarao:
Generative Image Inpainting with Submanifold Alignment. CoRR abs/1908.00211 (2019) - [i8]Yisen Wang, Xingjun Ma, Zaiyi Chen, Yuan Luo, Jinfeng Yi, James Bailey:
Symmetric Cross Entropy for Robust Learning with Noisy Labels. CoRR abs/1908.06112 (2019) - 2018
- [b1]Xingjun Ma:
Machine learning with adversarial perturbations and noisy labels. University of Melbourne, Parkville, Victoria, Australia, 2018 - [c10]Sudanthi N. R. Wijewickrema, Xingjun Ma, Patorn Piromchai, Robert Briggs, James Bailey, Gregor E. Kennedy, Stephen J. O'Leary:
Providing Automated Real-Time Technical Feedback for Virtual Reality Based Surgical Training: Is the Simpler the Better? AIED (1) 2018: 584-598 - [c9]Sudanthi N. R. Wijewickrema, Bridget Copson, Xingjun Ma, Robert Briggs, James Bailey, Gregor E. Kennedy, Stephen J. O'Leary:
Development and Validation of a Virtual Reality Tutor to Teach Clinically Oriented Surgical Anatomy of the Ear. CBMS 2018: 12-17 - [c8]Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia:
Iterative Learning With Open-Set Noisy Labels. CVPR 2018: 8688-8696 - [c7]Xingjun Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi N. R. Wijewickrema, Grant Schoenebeck, Dawn Song, Michael E. Houle, James Bailey:
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality. ICLR 2018 - [c6]Xingjun Ma, Yisen Wang, Michael E. Houle, Shuo Zhou, Sarah M. Erfani, Shu-Tao Xia, Sudanthi N. R. Wijewickrema, James Bailey:
Dimensionality-Driven Learning with Noisy Labels. ICML 2018: 3361-3370 - [i7]Xingjun Ma, Bo Li, Yisen Wang, Sarah M. Erfani, Sudanthi N. R. Wijewickrema, Michael E. Houle, Grant Schoenebeck, Dawn Song, James Bailey:
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality. CoRR abs/1801.02613 (2018) - [i6]Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia:
Iterative Learning with Open-set Noisy Labels. CoRR abs/1804.00092 (2018) - [i5]Xingjun Ma, Yisen Wang, Michael E. Houle, Shuo Zhou, Sarah M. Erfani, Shu-Tao Xia, Sudanthi N. R. Wijewickrema, James Bailey:
Dimensionality-Driven Learning with Noisy Labels. CoRR abs/1806.02612 (2018) - 2017
- [c5]Yisen Wang, Simone Romano, Vinh Nguyen, James Bailey, Xingjun Ma, Shu-Tao Xia:
Unbiased Multivariate Correlation Analysis. AAAI 2017: 2754-2760 - [c4]Xingjun Ma, Sudanthi N. R. Wijewickrema, Yun Zhou, Bridget Copson, James Bailey, Gregor E. Kennedy, Stephen J. O'Leary:
Simulation for Training Cochlear Implant Electrode Insertion. CBMS 2017: 1-6 - [c3]Sudanthi N. R. Wijewickrema, Bridget Copson, Yun Zhou, Xingjun Ma, Robert Briggs, James Bailey, Gregor E. Kennedy, Stephen J. O'Leary:
Design and Evaluation of a Virtual Reality Simulation Module for Training Advanced Temporal Bone Surgery. CBMS 2017: 7-12 - [c2]Xingjun Ma, Sudanthi N. R. Wijewickrema, Shuo Zhou, Yun Zhou, Zakaria Mhammedi, Stephen J. O'Leary, James Bailey:
Adversarial Generation of Real-time Feedback with Neural Networks for Simulation-based Training. IJCAI 2017: 3763-3769 - [c1]Xingjun Ma, Sudanthi N. R. Wijewickrema, Yun Zhou, Shuo Zhou, Stephen J. O'Leary, James Bailey:
Providing Effective Real-Time Feedback in Simulation-Based Surgical Training. MICCAI (2) 2017: 566-574 - [i4]Xingjun Ma, James Bailey, Sudanthi N. R. Wijewickrema, Shuo Zhou, Zakaria Mhammedi, Yun Zhou, Stephen J. O'Leary:
Extracting Real-time Feedback with Neural Networks for Simulation-based Learning. CoRR abs/1703.01460 (2017) - [i3]Xingjun Ma, Chunping Li, James Bailey, Sudanthi N. R. Wijewickrema:
Finding Influentials in Twitter: A Temporal Influence Ranking Model. CoRR abs/1703.01468 (2017) - [i2]Sudanthi N. R. Wijewickrema, Xingjun Ma, James Bailey, Gregor E. Kennedy, Stephen J. O'Leary:
Feedback Techniques in Computer-Based Simulation Training: A Survey. CoRR abs/1705.04683 (2017) - [i1]Xingjun Ma, Sudanthi N. R. Wijewickrema, Yun Zhou, Shuo Zhou, Stephen J. O'Leary, James Bailey:
Providing Effective Real-time Feedback in Simulation-based Surgical Training. CoRR abs/1706.10036 (2017)
Coauthor Index
[j10] [c64] [c57] [c56] [i78] [i77] [i75] [i73] [j8] [c54] [c49] [i57] [j5] [i44] [j3] [c39] [c34] [c33] [c30] [c27] [c26] [i43] [i41] [i39] [i38] [i33] [i29] [i26] [i23] [j2] [c23] [c22] [c21] [c20] [c18] [c17] [c16] [i22] [i21] [i20] [i19] [i18] [i17] [c14] [c13] [c11] [i13] [i12] [i10] [i8] [c10] [c9] [c8] [c7] [c6] [i7] [i6] [i5] [c5] [c4] [c3] [c2] [c1] [i4] [i3] [i2] [i1]
Sarah M. Erfani
aka: Sarah Monazam Erfani
aka: Sarah Monazam Erfani
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