1 citations · 1 across the 6 of their papers we have counts for
7 papers
Row-Centric Lossless Compression of Markov Images
Matthew G. Reyes, David L. Neuhoff
Motivated by the question of whether the recently introduced Reduced Cutset Coding (RCC) offers rate-complexity performance benefits over conventional context-based conditional cod…
Correct Convergence of Min-Sum Loopy Belief Propagation in a Block Interpolation Problem
Yutong Wang, Matthew G. Reyes, David L. Neuhoff
This work proves a new result on the correct convergence of Min-Sum Loopy Belief Propagation (LBP) in an interpolation problem on a square grid graph. The focus is on the notion of…
Cutset Width and Spacing for Reduced Cutset Coding of Markov Random Fields
Matthew G. Reyes, David L. Neuhoff
In this paper we explore tradeoffs, regarding coding performance, between the thickness and spacing of the cutset used in Reduced Cutset Coding (RCC) of a Markov random field image…
Minimum Conditional Description Length Estimation for Markov Random Fields
Matthew G. Reyes, David L. Neuhoff
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…
Multidimensional Manhattan Sampling and Reconstruction
Matthew A. Prelee, David L. Neuhoff
This paper introduces Manhattan sampling in two and higher dimensions, and proves sampling theorems. In two dimensions, Manhattan sampling, which takes samples densely along a Manh…
Throughput Scaling in Random Wireless Networks: A Non-Hierarchical Multipath Routing Strategy
Awlok Josan, Mingyan Liu, David L. Neuhoff +1
Franceschetti et al. have recently shown that per-node throughput in an extended, ad hoc wireless network with randomly distributed nodes and multihop routing can be increas…