The paper introduces risk-consistent multiclass learning from random label-subset queries by deriving an unbiased risk estimator under ERM, plus non-negative and absolute-value corrections, with generalization bounds and consistency results.
A brief introduction to weakly supervised learning
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Risk-Consistent Multiclass Learning from Random Label-Subset Membership Queries
The paper introduces risk-consistent multiclass learning from random label-subset queries by deriving an unbiased risk estimator under ERM, plus non-negative and absolute-value corrections, with generalization bounds and consistency results.