24 citations · 62 across the 35 of their papers we have counts for
8 papers · 1 filter
Progressive Generalization Risk Reduction for Data-Efficient Causal Effect Estimation
Hechuan Wen, Tong Chen, Guanhua Ye +3
Causal effect estimation (CEE) provides a crucial tool for predicting the unobserved counterfactual outcome for an entity. As CEE relaxes the requirement for ``perfect'' counterfac…
EMIT- Event-Based Masked Auto Encoding for Irregular Time Series
Hrishikesh Patel, Ruihong Qiu, Adam Irwin +2
Irregular time series, where data points are recorded at uneven intervals, are prevalent in healthcare settings, such as emergency wards where vital signs and laboratory results ar…
Fairness without Sensitive Attributes via Knowledge Sharing
Hongliang Ni, Lei Han, Tong Chen +2
While model fairness improvement has been explored previously, existing methods invariably rely on adjusting explicit sensitive attribute values in order to improve model fairness…
ID-Free Not Risk-Free: LLM-Powered Agents Unveil Risks in ID-Free Recommender Systems
Zongwei Wang, Min Gao, Junliang Yu +4
Recent advances in ID-free recommender systems have attracted significant attention for effectively addressing the cold start problem. However, their vulnerability to malicious att…
Poisoning Attacks and Defenses in Recommender Systems: A Survey
Zongwei Wang, Junliang Yu, Min Gao +4
Modern recommender systems (RS) have profoundly enhanced user experience across digital platforms, yet they face significant threats from poisoning attacks. These attacks, aimed at…
Large Language Models Meet User Interfaces: The Case of Provisioning Feedback
Stanislav Pozdniakov, Jonathan Brazil, Solmaz Abdi +5
Incorporating Generative AI (GenAI) and Large Language Models (LLMs) in education can enhance teaching efficiency and enrich student learning. Current LLM usage involves conversati…