2 citations · 4 across the 8 of their papers we have counts for
8 papers
Interpretable vs Learned Encoders for High-Cardinality Fraud Detection
Xiao Han, Jingjing Liu, Moxuan Zheng +2
A total of seven categorical encoding methods were tested on the IEEE-CIS fraud benchmark dataset (590,540 records, 3.5% positives, 8 high-cardinality columns). The encoders were e…
How Early Is Early Enough? Design-Dependent Observation-Window Sufficiency in Subscription Churn Prediction
Xiao Han, Yao Xiao, Chenyu Wu +1
How many days of early behavior suffice for subscription churn prediction? In the public KKBox dataset, the early indicator of churn is typically an indicator of someone's contract…
Validation-Stage Combinatorial Fusion Analysis for Imbalanced Credit-Card Fraud Detection
Xiao Han, Chenyu Wu
Credit-card fraud detection is difficult because fraudulent transactions are rare, costly, and unevenly distributed. Strong gradient-boosted tree models already perform well on str…
Decomposing Firm-Level Crisis Responses from Incomplete Market Signals: Evidence from China's IT Sector During COVID-19
Xiao Han, Yao Xiao
Exogenous shocks generate heterogeneous behavioral responses across firms, yet event studies typically report only sector-level averages. This paper develops a multi-method approac…
Algorithmic Recourse in Abnormal Multivariate Time Series
Xiao Han, Lu Zhang, Yongkai Wu +1
Algorithmic recourse provides actionable recommendations to alter unfavorable predictions of machine learning models, enhancing transparency through counterfactual explanations. Wh…
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…