Large Margin Distribution Machine

2013-11-05 · Teng Zhang, Zhi-Hua Zhou

Support vector machine (SVM) has been one of the most popular learning algorithms, with the central idea of maximizing the minimum margin, i.e., the smallest distance from the instances to the classification boundary. Recent theoretical results, however, disclosed that maximizing the minimum margin does not necessarily lead to better generalization performances, and instead, the margin distribution has been proven to be more crucial. In this paper, we propose the Large margin Distribution Machine (LDM), which tries to achieve a better generalization performance by optimizing the margin distribution. We characterize the margin distribution by the first- and second-order statistics, i.e., the margin mean and variance. The LDM is a general learning approach which can be used in any place where SVM can be applied, and its superiority is verified both theoretically and empirically in this paper.

📄 PDF Abstract BibTeX arXiv:1311.0989

Code (0)

등록된 구현이 없습니다.

Methods 이 논문이 사용한 방법론

SVM A Support Vector Machine, or SVM, is a non-parametric supervised learning model. For non-linear classification and regression, they utilise the kernel trick to map inputs…

Comparison theorems on large-margin learning

2019-08-13 · Jun Fan, Dao-Hong Xiang

This paper studies binary classification problem associated with a family of loss functions called large-margin unified machines (LUM), which offers a natural bridge between distribution-based likelihood approaches and m…

Binary Classification

Optimal Margin Distribution Machine

2016-04-12 · Teng Zhang, Zhi-Hua Zhou

Multi-Class Optimal Margin Distribution Machine

2017-08-01 · ICML 2017 8 · Teng Zhang, Zhi-Hua Zhou

Recent studies disclose that maximizing the minimum margin like support vector machines does not necessarily lead to better generalization performances, and instead, it is crucial to optimize the margin distribution…

Binary Classification Classification General Classification Multi-class Classification

Scalable Optimal Margin Distribution Machine

2023-05-08 · Yilin Wang, Nan Cao, Teng Zhang, Xuanhua Shi 외

Optimal margin Distribution Machine (ODM) is a newly proposed statistical learning framework rooting in the novel margin theory, which demonstrates better generalization performance than the traditional large margin base…

Distributed Optimal Margin Distribution Machine

2021-09-29 · Yilin Wang, Nan Cao, Teng Zhang, Hai Jin

Optimal margin Distribution Machine (ODM), a newly proposed statistical learning framework rooting in the novel margin theory, demonstrates better generalization performance than the traditional large margin based counte…