102 research outputs found

    Recognizing Graph Theoretic Properties with Polynomial Ideals

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    Many hard combinatorial problems can be modeled by a system of polynomial equations. N. Alon coined the term polynomial method to describe the use of nonlinear polynomials when solving combinatorial problems. We continue the exploration of the polynomial method and show how the algorithmic theory of polynomial ideals can be used to detect k-colorability, unique Hamiltonicity, and automorphism rigidity of graphs. Our techniques are diverse and involve Nullstellensatz certificates, linear algebra over finite fields, Groebner bases, toric algebra, convex programming, and real algebraic geometry.Comment: 20 pages, 3 figure

    Proof of the cases p7p \leq 7 of the Lieb-Seiringer formulation of the Bessis-Moussa-Villani conjecture

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    It is shown that the polynomial λ(t)=Tr[(A+tB)p]\lambda(t) = {\rm Tr}[(A + tB)^p] has nonnegative coefficients when p7p \leq 7 and A and B are any two complex positive semidefinite n×nn \times n matrices with arbitrary nn. This proofs a general nontrivial case of the Lieb-Seiringer formulation of the Bessis-Moussa-Villani conjecture which is a long standing problem in theoretical physics.Comment: 5 pages; typos corrected; accepted for publication in Journal of Statistical Physic

    Statistical Inference in a Directed Network Model with Covariates

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    Networks are often characterized by node heterogeneity for which nodes exhibit different degrees of interaction and link homophily for which nodes sharing common features tend to associate with each other. In this paper, we propose a new directed network model to capture the former via node-specific parametrization and the latter by incorporating covariates. In particular, this model quantifies the extent of heterogeneity in terms of outgoingness and incomingness of each node by different parameters, thus allowing the number of heterogeneity parameters to be twice the number of nodes. We study the maximum likelihood estimation of the model and establish the uniform consistency and asymptotic normality of the resulting estimators. Numerical studies demonstrate our theoretical findings and a data analysis confirms the usefulness of our model.Comment: 29 pages. minor revisio

    Four lectures on secant varieties

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    This paper is based on the first author's lectures at the 2012 University of Regina Workshop "Connections Between Algebra and Geometry". Its aim is to provide an introduction to the theory of higher secant varieties and their applications. Several references and solved exercises are also included.Comment: Lectures notes to appear in PROMS (Springer Proceedings in Mathematics & Statistics), Springer/Birkhause

    Rank Analysis of Cubic Multivariate Cryptosystems

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    In this work we analyze the security of cubic cryptographic constructions with respect to rank weakness. We detail how to extend the big field idea from quadratic to cubic, and show that the same rank defect occurs. We extend the min-rank problem and propose an algorithm to solve it in this setting. We show that for fixed small rank, the complexity is even lower than for the quadratic case. However, the rank of a cubic polynomial in nn variables can be larger than nn, and in this case the algorithm is very inefficient. We show that the rank of the differential is not necessarily smaller, rendering this line of attack useless if the rank is large enough. Similarly, the algebraic attack is exponential in the rank, thus useless for high rank

    Microsoft Silverlight 4 and SharePoint 2010 Integration

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    Techniques, practical tips, hints, and tricks for Microsoft Silverlight 4 interactions with SharePoint 2010 in this book and eBoo

    Learning object-oriented programming

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    If you're a Python, JavaScript, or C# developer and want to learn the basics of object-oriented programming with real-world examples, then this book is for you
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