Multi-view partial label machine

In partial label learning (PLL), each instance is associated with a set of candidate labels, among which there is only ground-truth label. PLL aims to identify the ground-truth label out of these candidate labels. Most of the existing PLL approaches are proposed to handle the single-view PLL problem, and the multi-view PLL problem has not been addressed. In this paper, we propose a novel multi-view paunknown. (c) 2021 Elsevier Inc. All rights reserved.

Automated summary

"PLL is a method for handling partial label learning, aiming to identify the ground-truth label from a set of candidate labels. Most existing PLL approaches focus on the single-view problem and do not address the multi-view problem. This paper proposes a novel multi-view paunknown method."