145 citations · 237 across the 17 of their papers we have counts for
17 papers
Learning from Heterogeneity: A Dynamic Learning Framework for Hypergraphs
Tiehua Zhang, Yuze Liu, Zhishu Shen +4
Graph neural network (GNN) has gained increasing popularity in recent years owing to its capability and flexibility in modeling complex graph structure data. Among all graph learni…
Reconstructive Neuron Pruning for Backdoor Defense
Yige Li, Xixiang Lyu, Xingjun Ma +4
Deep neural networks (DNNs) have been found to be vulnerable to backdoor attacks, raising security concerns about their deployment in mission-critical applications. While existing…
Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models
Zhiyuan Zhang, Lingjuan Lyu, Xingjun Ma +2
Deep Neural Networks (DNNs) are known to be vulnerable to backdoor attacks. In Natural Language Processing (NLP), DNNs are often backdoored during the fine-tuning process of a larg…
Backdoor Attacks on Crowd Counting
Yuhua Sun, Tailai Zhang, Xingjun Ma +6
Crowd counting is a regression task that estimates the number of people in a scene image, which plays a vital role in a range of safety-critical applications, such as video surveil…
CalFAT: Calibrated Federated Adversarial Training with Label Skewness
Chen Chen, Yuchen Liu, Xingjun Ma +1
Recent studies have shown that, like traditional machine learning, federated learning (FL) is also vulnerable to adversarial attacks. To improve the adversarial robustness of FL, f…
Bulk carrier lifetime surpassing 600 us in Upgraded Metallurgical-grade Silicon multicrystalline wafers after Phosphorus Diffusion Gettering
Nerea Dasilva-Villanueva, Sergio Catalán-Gómez, David Fuertes Marrón +2
Upgraded metallurgical-grade (UMG) Si is obtained via a purification route alternative to the one used for conventional polysilicon and with significantly reduced environmental imp…
SpineOne: A One-Stage Detection Framework for Degenerative Discs and Vertebrae
Jiabo He, Wei Liu, Yu Wang +2
Spinal degeneration plagues many elders, office workers, and even the younger generations. Effective pharmic or surgical interventions can help relieve degenerative spine condition…
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
Jiabo He, Sarah Erfani, Xingjun Ma +3
Bounding box (bbox) regression is a fundamental task in computer vision. So far, the most commonly used loss functions for bbox regression are the Intersection over Union (IoU) los…
ECG-ATK-GAN: Robustness against Adversarial Attacks on ECGs using Conditional Generative Adversarial Networks
Khondker Fariha Hossain, Sharif Amit Kamran, Alireza Tavakkoli +1
Automating arrhythmia detection from ECG requires a robust and trusted system that retains high accuracy under electrical disturbances. Many machine learning approaches have reache…
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
Hanxun Huang, Yisen Wang, Sarah Monazam Erfani +3
Deep neural networks (DNNs) are known to be vulnerable to adversarial attacks. A range of defense methods have been proposed to train adversarially robust DNNs, among which adversa…
Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better
Bojia Zi, Shihao Zhao, Xingjun Ma +1
Adversarial training is one effective approach for training robust deep neural networks against adversarial attacks. While being able to bring reliable robustness, adversarial trai…
Sub-trajectory Similarity Join with Obfuscation
Yanchuan Chang, Jianzhong Qi, Egemen Tanin +2
User trajectory data is becoming increasingly accessible due to the prevalence of GPS-equipped devices such as smartphones. Many existing studies focus on querying trajectories tha…
Noise Doesn't Lie: Towards Universal Detection of Deep Inpainting
Ang Li, Qiuhong Ke, Xingjun Ma +4
Deep image inpainting aims to restore damaged or missing regions in an image with realistic contents. While having a wide range of applications such as object removal and image rec…
Dual Head Adversarial Training
Yujing Jiang, Xingjun Ma, Sarah Monazam Erfani +1
Deep neural networks (DNNs) are known to be vulnerable to adversarial examples/attacks, raising concerns about their reliability in safety-critical applications. A number of defens…
Anomaly Detection for Scenario-based Insider Activities using CGAN Augmented Data
R G Gayathri, Atul Sajjanhar, Yong Xiang +1
Insider threats are the cyber attacks from within the trusted entities of an organization. Lack of real-world data and issue of data imbalance leave insider threat analysis an unde…
Practical Privacy Attacks on Vertical Federated Learning
Haiqin Weng, Juntao Zhang, Xingjun Ma +4
Federated learning (FL) is a privacy-preserving learning paradigm that allows multiple parities to jointly train a powerful machine learning model without sharing their private dat…
Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness
Xingjun Ma, Linxi Jiang, Hanxun Huang +3
Evaluating the robustness of a defense model is a challenging task in adversarial robustness research. Obfuscated gradients have previously been found to exist in many defense meth…