Basics of Graph Limit Theory

2017 ◽  
pp. 27-41
Author(s):  
Sourav Chatterjee
Keyword(s):  
Limit Theory ◽  
Graph Limit

scholarly journals Constant-Time Algorithms for Continuous Optimization Problems

2021 ◽  
pp. 31-45
Author(s):  
Yuichi Yoshida
Keyword(s):  
Machine Learning ◽  
Optimization Problems ◽  
Continuous Optimization ◽  
Quadratic Function ◽  
Tensor Decomposition ◽  
Constant Time ◽  
Limit Theory ◽  
Graph Limit ◽  
Continuous Optimization Problems ◽  
Constant Time Algorithms

AbstractIn this chapter, we consider constant-time algorithms for continuous optimization problems. Specifically, we consider quadratic function minimization and tensor decomposition, both of which have numerous applications in machine learning and data mining. The key component in our analysis is graph limit theory, which was originally developed to study graphs analytically.

scholarly journals Action convergence of operators and graphs

2020 ◽  
pp. 1-50
Author(s):  
Ágnes Backhausz ◽  
Balázs Szegedy
Keyword(s):  
Matrix Theory ◽  
Point Of View ◽  
Bounded Operators ◽  
Compactness Result ◽  
New Approach ◽  
Limit Theory ◽  
Graph Limits ◽  
Graph Limit ◽  
Probability Spaces ◽  
Convergence Of Operators

Abstract We present a new approach to graph limit theory that unifies and generalizes the two most well-developed directions, namely dense graph limits (even the more general $L^p$ limits) and Benjamini–Schramm limits (even in the stronger local-global setting). We illustrate by examples that this new framework provides a rich limit theory with natural limit objects for graphs of intermediate density. Moreover, it provides a limit theory for bounded operators (called P-operators) of the form $L^\infty (\Omega )\to L^1(\Omega )$ for probability spaces $\Omega $ . We introduce a metric to compare P-operators (for example, finite matrices) even if they act on different spaces. We prove a compactness result, which implies that, in appropriate norms, limits of uniformly bounded P-operators can again be represented by P-operators. We show that limits of operators, representing graphs, are self-adjoint, positivity-preserving P-operators called graphops. Graphons, $L^p$ graphons, and graphings (known from graph limit theory) are special examples of graphops. We describe a new point of view on random matrix theory using our operator limit framework.

Limit of a nonpreferential attachment multitype network model

2017 ◽  
Vol 31 (05) ◽  
pp. 1750026 ◽  
Author(s):  
Yilun Shang
Keyword(s):  
Complex Networks ◽  
Network Model ◽  
Theoretical Framework ◽  
Network Size ◽  
Temporal Networks ◽  
Limit Theory ◽  
Time Order ◽  
Graph Limit

Here, we deal with a model of multitype network with nonpreferential attachment growth. The connection between two nodes depends asymmetrically on their types, reflecting the implication of time order in temporal networks. Based upon graph limit theory, we analytically determined the limit of the network model characterized by a kernel, in the sense that the number of copies of any fixed subgraph converges when network size tends to infinity. The results are confirmed by extensive simulations. Our work thus provides a theoretical framework for quantitatively understanding grown temporal complex networks as a whole.

scholarly journals Massive gravity from double copy

2020 ◽  
Vol 2020 (12) ◽  
Author(s):  
Arshia Momeni ◽  
Justinas Rumbutis ◽  
Andrew J. Tolley
Keyword(s):  
Sigma Model ◽  
Massive Gravity ◽  
Effective Field ◽  
Effective Theory ◽  
Nonlinear Sigma Model ◽  
Limit Theory ◽  
Four Dimensions ◽  
Yang Mills ◽  
Massive Spin ◽  
Double Copy

Abstract We consider the double copy of massive Yang-Mills theory in four dimensions, whose decoupling limit is a nonlinear sigma model. The latter may be regarded as the leading terms in the low energy effective theory of a heavy Higgs model, in which the Higgs has been integrated out. The obtained double copy effective field theory contains a massive spin-2, massive spin-1 and a massive spin-0 field, and we construct explicitly its interacting Lagrangian up to fourth order in fields. We find that up to this order, the spin-2 self interactions match those of the dRGT massive gravity theory, and that all the interactions are consistent with a Λ3 = (m2MPl)1/3 cutoff. We construct explicitly the Λ3 decoupling limit of this theory and show that it is equivalent to a bi-Galileon extension of the standard Λ3 massive gravity decoupling limit theory. Although it is known that the double copy of a nonlinear sigma model is a special Galileon, the decoupling limit of massive Yang-Mills theory is a more general Galileon theory. This demonstrates that the decoupling limit and double copy procedures do not commute and we clarify why this is the case in terms of the scaling of their kinematic factors.

scholarly journals Limit theory for multivariate sample extremes

1977 ◽  
Vol 40 (4) ◽  
pp. 317-337 ◽  
Author(s):  
Laurens Haan ◽  
Sidney I. Resnick
Keyword(s):  
Limit Theory ◽  
Multivariate Sample

scholarly journals LIMIT THEORY FOR COINTEGRATED SYSTEMS WITH MODERATELY INTEGRATED AND MODERATELY EXPLOSIVE REGRESSORS

2009 ◽  
Vol 25 (2) ◽  
pp. 482-526 ◽  
Author(s):  
Tassos Magdalinos ◽  
Peter C.B. Phillips
Keyword(s):  
Multivariate Regression ◽  
Cauchy Type ◽  
Tail Behavior ◽  
Least Squares Regression ◽  
Moment Conditions ◽  
Limit Theory ◽  
Asymptotically Normal ◽  
Significant Bias ◽  
Integrated Or ◽  
Special Case

An asymptotic theory is developed for multivariate regression in cointegrated systems whose variables are moderately integrated or moderately explosive in the sense that they have autoregressive roots of the form ρni = 1 + ci/nα, involving moderate deviations from unity when α ∈ (0, 1) and ci ∈ ℝ are constant parameters. When the data are moderately integrated in the stationary direction (with ci < 0), it is shown that least squares regression is consistent and asymptotically normal but suffers from significant bias, related to simultaneous equations bias. In the moderately explosive case (where ci > 0) the limit theory is mixed normal with Cauchy-type tail behavior, and the rate of convergence is explosive, as in the case of a moderately explosive scalar autoregression (Phillips and Magdalinos, 2007, Journal of Econometrics 136, 115–130). Moreover, the limit theory applies without any distributional assumptions and for weakly dependent errors under conventional moment conditions, so an invariance principle holds, unlike the well-known case of an explosive autoregression. This theory validates inference in cointegrating regression with mildly explosive regressors. The special case in which the regressors themselves have a common explosive component is also considered.

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