1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2021★ 1 cited
Leveraged Weighted Loss for Partial Label Learning
Hongwei Wen, Jingyi Cui, Hanyuan Hang +3
As an important branch of weakly supervised learning, partial label learning deals with data where each instance is assigned with a set of candidate labels, whereas only one of the…
cs.LG2021
Two-stage Training for Learning from Label Proportions
Jiabin Liu, Bo Wang, Xin Shen +2
Learning from label proportions (LLP) aims at learning an instance-level classifier with label proportions in grouped training data. Existing deep learning based LLP methods utiliz…
cs.LG2019
Learning from Label Proportions with Generative Adversarial Networks
Jiabin Liu, Bo Wang, Zhiquan Qi +2
In this paper, we leverage generative adversarial networks (GANs) to derive an effective algorithm LLP-GAN for learning from label proportions (LLP), where only the bag-level propo…