...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>New Generation Computing >Fast Co-MLM: An Efficient Semi-supervised Co-training Method Based on the Minimal Learning Machine
【24h】

Fast Co-MLM: An Efficient Semi-supervised Co-training Method Based on the Minimal Learning Machine

机译：快速Co-MLM：基于最小学习机的高效半监督协同训练方法

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

AbstractCo-training is a framework for semi-supervised learning that has attracted much attention due to its good performance and easy adaptation for various learning algorithms. In a recent work, Caldas et al. proposed a co-training-based method using the recently proposed supervised learning method named minimal learning machine (MLM). Although the proposed method, referred to as Co-MLM, presented results that are comparable to other semi-supervised algorithms, using MLM as a base learner resulted in a formulation with heavy computational cost. Aiming to mitigate this problem, in this paper, we propose an improved variant of Co-MLM with reduced computational cost on both training and testing phases. The proposed method is compared to Co-MLM and other Co-training-based semi-supervised methods, presenting comparable performances.
机译： Abstract 协同培训是半监督学习的框架，引起了广泛关注由于其良好的性能，并且易于适应各种学习算法。在最近的工作中，Caldas等人。提出了一种基于协作训练的方法，该方法使用了最近提出的名为最小学习机（MLM）的监督学习方法。尽管所提出的方法称为Co-MLM，其结果可与其他半监督算法相媲美，但使用MLM作为基础学习器却导致计算量大。为了减轻这个问题，在本文中，我们提出了一种改进的Co-MLM变体，在训练和测试阶段都降低了计算成本。将该方法与Co-MLM和其他基于Co-training的半监督方法进行了比较，具有可比的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号