Gaussian Multiresolution Models: Exploiting Sparse Markov and Covariance Structure

In this paper, we consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale, and the coarser, hidden variables serve to capture long-distance dependencies. Tree-structured MR models have limited modeling capabilities, as variables at o...

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书目详细资料
Main Authors: Choi, Myung Jin, Chandrasekaran, Venkat, Willsky, Alan S.
其他作者: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
格式: 文件
语言:en_US
出版: Institute of Electrical and Electronics Engineers 2010
主题:
在线阅读:http://hdl.handle.net/1721.1/58956
https://orcid.org/0000-0003-0149-5888