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Search Publications by: Brian D. Cloteaux (Fed)

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Displaying 26 - 46 of 46

Counting the Leaves of Trees

December 19, 2011
Author(s)
Brian D. Cloteaux, Luis A. Valentin
A number of important combinatorial counting problems can be reformulated into the problem of counting the number of leaf nodes on a tree. Since the basic leaf-counting problem is #P-complete, there is strong evidence that no polynomial time algorithm

Extracting Hierarchies With Overlapping Structure From Network Data

December 11, 2011
Author(s)
Brian D. Cloteaux
Relationships between entities in many complex systems, such as the Internet and social networks, have a natural hierarchical organization. Understanding these inherent hierarchies is essential for creating models of these systems. Thus, there is a recent

Approximating the Number of Bases for Almost All Matroids

February 1, 2011
Author(s)
Brian D. Cloteaux
We define a class of matroids A for which a fully polynomial randomized approximation scheme (fpras) exists for counting the number of bases of the matroids. We then show that as the number of elements in a matroid increases, the probability that a matroid

Modeling Affiliations in Networks

December 6, 2010
Author(s)
Brian D. Cloteaux
One way to help understand the structure of certain networks is to examine what common group memberships the actors in the network share. Linking actors to their common affiliations gives an alternative type of network commonly called an affiliation

Matching Observed Alpha Helix Lengths to Predicted Secondary Structure

October 11, 2010
Author(s)
Brian D. Cloteaux
Because of the complexity in determining the 3D structure of a protein, the use of partial information determined from experimental techniques can greatly reduce the overall computational expense. We investigate the problem of matching experimentally

An Approximation Algorithm for the Coefficients of the Reliability Polynomial

March 15, 2010
Author(s)
Brian D. Cloteaux, Isabel M. Beichl, F Sullivan
The reliability polynomial gives the probability that a graph remains connected given that each edge in it can fail independently with a probability p. While in general determining the coefficients of this polynomial is #P-complete, we give a randomized

A Structural Approach to the Temporal Modeling of Networks

December 14, 2009
Author(s)
Brian D. Cloteaux, Isabel M. Beichl
Simulation of many dynamic real world systems such as the Internet and social networks requires developing dynamic models for the underlying networks in these systems. Currently, there is a large body of work devoted towards determining the underlying

Matching Observed Alpha Helix Lengths to Predicted Secondary Structure

November 1, 2009
Author(s)
Brian D. Cloteaux, Nadezhda Serova
Because of the complexity in determining the 3D structure of a protein, the use of partial information determined from experimental techniques can greatly reduce the overall computational expense. We investigate the problem of matching experimentally

Lower Bounds for Accessing Information on Pure Pointer Machines

July 13, 2009
Author(s)
Brian D. Cloteaux, Desh Ranjan
We study the complexity of representing an array on a Pure Pointer Machine (PPM) or a pointer machine without arithmetic capabilities. In particular, we show that lower bounds in access time for information retrieval on a PPM arise from two different

Measuring the Effectiveness of the s-Metric to Produce Better Network Models

December 7, 2008
Author(s)
Isabel M. Beichl, Brian D. Cloteaux
Recent research has shown that while many complex networks follow a power-law distribution for their vertex degrees, it is not sufficient to model these networks based only on their degree distribution. In order to better distinguish between these networks

Generating Network Models Using the S-Metric

July 14, 2008
Author(s)
Isabel M. Beichl, Brian D. Cloteaux
The ability to create random models of real networks is useful for understanding the interactions of the networks. Several researchers have proposed modeling of complex networks using the degree distribution, the most popular being a power-law distribution