3 papers
cs.LG2025
Multi-Instance Partial-Label Learning with Margin Adjustment
Wei Tang, Yin-Fang Yang, Zhaofei Wang +2
Multi-instance partial-label learning (MIPL) is an emerging learning framework where each training sample is represented as a multi-instance bag associated with a candidate label s…
stat.ML2024
HACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing Risks
Xin Liu, Weijia Zhang, Min-Ling Zhang
In survival analysis, subjects often face competing risks; for example, individuals with cancer may also suffer from heart disease or other illnesses, which can jointly influence t…
cs.LG2024
Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning
Wei Tang, Weijia Zhang, Min-Ling Zhang
Multi-instance partial-label learning (MIPL) addresses scenarios where each training sample is represented as a multi-instance bag associated with a candidate label set containing…