Risk-Consistent Multiclass Learning from Random Label-Subset Membership Queries
Obtaining accurate class labels is often costly or unreliable, and may also be limited by privacy or other practical conditions. Compared with asking an annotator to provide the exact class, it is often easier to ask whether the true label belongs to a certain label subset. This query-response form defines a distinct weak-supervision mechanism: weak supervision information is generated through feedback on a label subset. Although weakly supervised learning has studied many learning frameworks, most existing work starts from established weak label objects. A systematic characterization is still lacking for weakly supervised learning generated directly by such query response observations. T...
| Authors | Jiaxu Su, Junpeng Li, Changchun Hua et al. |
|---|---|
| Primary category | cs.LG |
| Published | 8 May 2026 |
| Last updated at source | 8 May 2026 |
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