20,467 research outputs found
Review of Benedict Anderson, 'Under Three Flags: Anarchism and the anti-colonial imagination' (London: Verso, 2005)
Row-Centric Lossless Compression of Markov Images
Motivated by the question of whether the recently introduced Reduced Cutset
Coding (RCC) offers rate-complexity performance benefits over conventional
context-based conditional coding for sources with two-dimensional Markov
structure, this paper compares several row-centric coding strategies that vary
in the amount of conditioning as well as whether a model or an empirical table
is used in the encoding of blocks of rows. The conclusion is that, at least for
sources exhibiting low-order correlations, 1-sided model-based conditional
coding is superior to the method of RCC for a given constraint on complexity,
and conventional context-based conditional coding is nearly as good as the
1-sided model-based coding.Comment: submitted to ISIT 201
Minimum Conditional Description Length Estimation for Markov Random Fields
In this paper we discuss a method, which we call Minimum Conditional
Description Length (MCDL), for estimating the parameters of a subset of sites
within a Markov random field. We assume that the edges are known for the entire
graph . Then, for a subset , we estimate the parameters
for nodes and edges in as well as for edges incident to a node in , by
finding the exponential parameter for that subset that yields the best
compression conditioned on the values on the boundary . Our
estimate is derived from a temporally stationary sequence of observations on
the set . We discuss how this method can also be applied to estimate a
spatially invariant parameter from a single configuration, and in so doing,
derive the Maximum Pseudo-Likelihood (MPL) estimate.Comment: Information Theory and Applications (ITA) workshop, February 201
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