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ConceptMIL / Multiple Instance Learning

Multiple Instance Learning (MIL)

A weakly supervised learning paradigm in which training labels are attached at the bag level rather than to individual instances. It is widely applied in drug activity prediction, medical imaging, and behavior analysis.

Timeline (last 90 days)

Oct 4

Multiple instance learning (MIL) represents each student as a bag containing a large amount of weakly labeled interaction behavior data, with a reinforcement learning agent responsible for selecting the most informative instances for use by the downstream classifier.

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Multiple instance learning (MIL) represents each student as a bag containing a large amount of weakly labeled interaction behavior data, with a reinforcement learning agent responsible for selecting the most informative instances for use by the downstream classifier.

50%

Source Articles

Fairness Meets Explainability: The Challenges of a Reinforcement Learning Multi-Instance Student Early Warning SystemOct 4