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cs.LG2024
ProPML: Probability Partial Multi-label Learning
Łukasz Struski, Adam Pardyl, Jacek Tabor +1
Partial Multi-label Learning (PML) is a type of weakly supervised learning where each training instance corresponds to a set of candidate labels, among which only some are true. In…
cs.LG2021★ 6 cited
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification
Dawid Rymarczyk, Adam Pardyl, Jarosław Kraus +3
Multiple Instance Learning (MIL) gains popularity in many real-life machine learning applications due to its weakly supervised nature. However, the corresponding effort on explaini…