43 citations · 95 across the 20 of their papers we have counts for
26 papers
Poisoning Attacks on Fair Machine Learning
Minh-Hao Van, Wei Du, Xintao Wu +1
Both fair machine learning and adversarial learning have been extensively studied. However, attacking fair machine learning models has received less attention. In this paper, we pr…
Fair Regression under Sample Selection Bias
Wei Du, Xintao Wu, Hanghang Tong
Recent research on fair regression focused on developing new fairness notions and approximation methods as target variables and even the sensitive attribute are continuous in the r…
Achieving Counterfactual Fairness for Causal Bandit
Wen Huang, Lu Zhang, Xintao Wu
In online recommendation, customers arrive in a sequential and stochastic manner from an underlying distribution and the online decision model recommends a chosen item for each arr…
Robust Fairness-aware Learning Under Sample Selection Bias
Wei Du, Xintao Wu
The underlying assumption of many machine learning algorithms is that the training data and test data are drawn from the same distributions. However, the assumption is often violat…
Classifying Math KCs via Task-Adaptive Pre-Trained BERT
Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar +4
Educational content labeled with proper knowledge components (KCs) are particularly useful to teachers or content organizers. However, manually labeling educational content is labo…
LogBERT: Log Anomaly Detection via BERT
Haixuan Guo, Shuhan Yuan, Xintao Wu
Detecting anomalous events in online computer systems is crucial to protect the systems from malicious attacks or malfunctions. System logs, which record detailed information of co…