...
首页> 外文期刊>Knowledge and Information Systems >Exponential family tensor factorization: an online extension and applications
【24h】

Exponential family tensor factorization: an online extension and applications

机译:指数族张量分解:在线扩展和应用

获取原文
获取原文并翻译 | 示例
           

摘要

In this paper, we propose a new probabilistic model of heterogeneously attributed multi-dimensional arrays. The model can manage heterogeneity by employing individual exponential family distributions for each attribute of the tensor array. Entries of the tensor are connected by latent variables and share information across the different attributes through the latent variables. The assumption of heterogeneity makes a Bayesian inference intractable, and we cast the EM algorithm approximated by the Laplace method and Gaussian process. We also extended the proposal algorithm for online learning. We apply our method to missing-values prediction and anomaly detection problems and show that our method outperforms conventional approaches that do not consider heterogeneity.
机译:在本文中,我们提出了一种异构属性多维数组的新概率模型。该模型可以通过对张量数组的每个属性采用单独的指数族分布来管理异质性。张量的条目由潜在变量连接,并通过潜在变量在不同属性之间共享信息。异质性的假设使贝叶斯推理变得难以处理,并且我们对通过Laplace方法和高斯过程近似的EM算法进行了转换。我们还扩展了在线学习的提案算法。我们将我们的方法应用于缺失值预测和异常检测问题,并表明我们的方法优于不考虑异构性的常规方法。

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