作者
Felix Yu, Dong Liu, Sanjiv Kumar, Jebara Tony, Shih-Fu Chang
发表日期
2013/5/26
研讨会论文
International Conference on Machine Learning
页码范围
504-512
出版商
PMLR
简介
We study the problem of learning with label proportions in which the training data is provided in groups and only the proportion of each class in each group is known. We propose a new method called proportion-SVM, or\proptoSVM, which explicitly models the latent unknown instance labels together with the known group label proportions in a large-margin framework. Unlike the existing works, our approach avoids making restrictive assumptions about the data. The\proptoSVM model leads to a non-convex integer programming problem. In order to solve it efficiently, we propose two algorithms: one based on simple alternating optimization and the other based on a convex relaxation. Extensive experiments on standard datasets show that\proptoSVM outperforms the state-of-the-art, especially for larger group sizes.
学术搜索中的文章
F Yu, D Liu, S Kumar, J Tony, SF Chang - International Conference on Machine Learning, 2013