Unsupervised Progressive Parsing of Poisson Fields Using Minimum Description Length, Criteria
نویسندگان
چکیده
This paper describes novel methods for estimating piecewise homogeneous Poisson elds based on minimum description length (MDL) criteria. By adopting a coding-theoretic approach, our methods are able to adapt to the the observed eld in an unsupervised manner. We present a parsing scheme based on xed multiscale trees (binary, for 1D, quad, for 2D) and an adaptive recursive partioning algorithm, both guided by MDL criteria. Experiments show that the recursive scheme outperforms the xed tree approaches.
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