Zhaofei Wang

Multi-Instance Partial-Label Learning with Margin Adjustment

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 set. Existing MIPL algorithms often overlook the margins for attention scores and predicted probabilities, leading to sub…