Partial-label Learning with Mixed Closed-set and Open-set Out-of-candidate Examples

Shuo He, Lei Feng, Guowu Yang

Partial-label learning (PLL) relies on a key assumption that the true label of each training example must be in the candidate label set. This restrictive assumption may be violated…