1 citations · 1 across the 12 of their papers we have counts for
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CAAL: Contextual Bandits based Online Hand-Craft Active Learning Strategy Selection
Shao-An Yin, Jiacong Li, Tianpei Xie +3
The challenge with active learning algorithms is the uncertainty of the statistical distribution of unlabeled data, making it difficult to choose the best hand-crafted strategy. To…
How Strategic Agents Respond: Comparing Analytical Models with LLM-Generated Responses in Strategic Classification
Tian Xie, Pavan Rauch, Xueru Zhang
When ML algorithms are deployed to automate human-related decisions, human agents may learn the underlying decision policies and adapt their behavior. Strategic Classification (SC)…
Lookahead Counterfactual Fairness
Zhiqun Zuo, Tian Xie, Xuwei Tan +2
As machine learning (ML) algorithms are used in applications that involve humans, concerns have arisen that these algorithms may be biased against certain social groups. \textit{Co…
ProFL: Performative Robust Optimal Federated Learning
Xue Zheng, Tian Xie, Xuwei Tan +2
Performative prediction is a framework that captures distribution shifts that occur during the training of machine learning models due to their deployment. As the trained model is…
Addressing Polarization and Unfairness in Performative Prediction
Kun Jin, Tian Xie, Yang Liu +1
In many real-world applications of machine learning such as recommendations, hiring, and lending, deployed models influence the data they are trained on, leading to feedback loops…
Automating Data Annotation under Strategic Human Agents: Risks and Potential Solutions
Tian Xie, Xueru Zhang
As machine learning (ML) models are increasingly used in social domains to make consequential decisions about humans, they often have the power to reshape data distributions. Human…