42 citations · 106 across the 20 of their papers we have counts for
11 papers · 1 filter
LogGPT: Log Anomaly Detection via GPT
Xiao Han, Shuhan Yuan, Mohamed Trabelsi
Detecting system anomalies based on log data is important for ensuring the security and reliability of computer systems. Recently, deep learning models have been widely used for lo…
Achieving Counterfactual Fairness for Anomaly Detection
Xiao Han, Lu Zhang, Yongkai Wu +1
Ensuring fairness in anomaly detection models has received much attention recently as many anomaly detection applications involve human beings. However, existing fair anomaly detec…
On Root Cause Localization and Anomaly Mitigation through Causal Inference
Xiao Han, Lu Zhang, Yongkai Wu +1
Due to a wide spectrum of applications in the real world, such as security, financial surveillance, and health risk, various deep anomaly detection models have been proposed and ac…
Fine-grained Anomaly Detection in Sequential Data via Counterfactual Explanations
He Cheng, Depeng Xu, Shuhan Yuan +1
Anomaly detection in sequential data has been studied for a long time because of its potential in various applications, such as detecting abnormal system behaviors from log data. A…
Trustworthy Anomaly Detection: A Survey
Shuhan Yuan, Xintao Wu
Anomaly detection has a wide range of real-world applications, such as bank fraud detection and cyber intrusion detection. In the past decade, a variety of anomaly detection models…
On the Convergence of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning
Che Wang, Shuhan Yuan, Kai Shao +1
A simple and natural algorithm for reinforcement learning (RL) is Monte Carlo Exploring Starts (MCES), where the Q-function is estimated by averaging the Monte Carlo returns, and t…
Identifying Hidden Buyers in Darknet Markets via Dirichlet Hawkes Process
Panpan Zheng, Shuhan Yuan, Xintao Wu +1
The darknet markets are notorious black markets in cyberspace, which involve selling or brokering drugs, weapons, stolen credit cards, and other illicit goods. To combat illicit tr…
Achieving Differential Privacy in Vertically Partitioned Multiparty Learning
Depeng Xu, Shuhan Yuan, Xintao Wu
Preserving differential privacy has been well studied under centralized setting. However, it's very challenging to preserve differential privacy under multiparty setting, especiall…
SAFE: A Neural Survival Analysis Model for Fraud Early Detection
Panpan Zheng, Shuhan Yuan, Xintao Wu
Many online platforms have deployed anti-fraud systems to detect and prevent fraudulent activities. However, there is usually a gap between the time that a user commits a fraudulen…
FairGAN: Fairness-aware Generative Adversarial Networks
Depeng Xu, Shuhan Yuan, Lu Zhang +1
Fairness-aware learning is increasingly important in data mining. Discrimination prevention aims to prevent discrimination in the training data before it is used to conduct predict…
One-Class Adversarial Nets for Fraud Detection
Panpan Zheng, Shuhan Yuan, Xintao Wu +2
Many online applications, such as online social networks or knowledge bases, are often attacked by malicious users who commit different types of actions such as vandalism on Wikipe…