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Multi-instance learning studies problems in which labels areassigned to bags that contain multiple instances. In these settings, the relations between instances and labels are usually ambiguous. Incontrast, multi-task learning focuses on the output space in whichan input sample is associated with multiple labels. In real world, asample may be associated with multiple labels that are derived fromobserving...
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