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Lecture Notes in Computer Science
In standard supervised learning, each training instance is associated with an outcome from a corresponding output space (e.g., a class label in classification or a real number in regression). In the superset learning problem, the outcome is only characterized in terms of a superset-a subset of candidates that covers the true outcome but may also contain additional ones. Thus, superset learning can be seen as a specific type of weakly supervised learning, in which training examples aredoi:10.1007/978-3-319-23525-7_16 fatcat:wul6brmiqrdmvf46x57tz2tt5e