Dynamic network models and graphon estimation
WebNov 21, 2024 · Pensky M (2016) Dynamic network models and graphon estimation. arXiv preprint arXiv:1607.00673. Fortunato S (2009) Community detection in graphs. Phys Rep 486(3):75–174. MathSciNet Google Scholar Xie J, Kelley S, Szymanski BK (2011) Overlapping community detection in networks: the state-of-the-art and comparative study. Webthe smoothness of the graphon is small, the minimax rate of graphon estimation is identical to that of nonparametric regression. This is surprising, since graphon Received October 2014; revised June 2015. MSC2010 subject classifications. 60G05. Key words and phrases. Network, graphon, stochastic block model, nonparametric regression, …
Dynamic network models and graphon estimation
Did you know?
WebWe propose a general approach for change-point detection in dynamic networks. The proposed method is model-free and covers a wide range of dynamic networks. The key idea behind our approach is to effectively utilize the network structure in designing change-point detection algorithms. This is done via an initial step of graphon estimation, where … WebDec 28, 2024 · Dynamic network models and graphon estimation. Article. Full-text available. Jul 2016; ANN STAT; Marianna Pensky; In the present paper we consider a dynamic stochastic network model. The objective ...
WebDynamic networkmodelsandgraphonestimation MariannaPensky DepartmentofMathematics,UniversityofCentralFlorida Abstract In the present paper we … WebApr 19, 2024 · Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic network models, network sampling, and network statistics such as sparsity and power law, all of which play a central role in contemporary data science and machine learning applications. ... Graphon estimation . …
Webdescribed by a stochastic block model with a fixed number of blocks. In this paper we consider nonparametric models (where the number of parameters need not be fixed or even finite) given in terms of a graphon. A graphon is a measurable, bounded function W: [0;1]2![0;1) such that W(x;y) = W(y;x), which for convenience we take to be ...
WebNonparametric methods for undirected networks have focused on estimation of the graphon model. While the graphon model accounts for nodal heterogeneity, it does not account for network heterogeneity, a feature speci c to applications where multiple networks are observed. To address this setting of multiple networks, we propose a multi-graphon …
WebThe model with such observations A =(Aij,1≤j campingplatz spreewald 5 sterneWebJan 1, 2024 · Dynamic network models and graphon estimation. The Annals of Statistics, 47(4):2378-2403, 2024. Google Scholar; Karl Rohe, Sourav Chatterjee, and Bin Yu. … campingplatz seeblick ostseeApr 19, 2024 · campingplatz rügen am wasserWeb1 day ago · Models will be able to solve previously unseen problems simply by having new tasks explained to them (dynamic task specification), without needing to be retrained … campingplatz rueppenhof thierseeWebOracle inequalities for network models and sparse graphon estimation. The Annals of Statistics, 45(1):316-354, 2024. Google Scholar; E. D. Kolaczyk and G. Csárdi. Statistical analysis of network data with R, Use R! book series, volume 65. Springer, 2014. ... Dynamic network models and graphon estimation. The Annals of Statistics, 47 … campingplatz spa francorchampsWebWe show that they satisfy oracle inequalities with respect to the block constant oracle. As a consequence, we derive optimal rates of estimation of the probability matrix. Our results cover the important setting of sparse networks. Another consequence consists in establishing upper bounds on the minimax risks for graphon estimation in the L2 ... campingplatz roermond am seeWebThe graphon provides a not-so-comprehensive list of methods for estimating graphon, a symmet-ric measurable function, from a single or multiple of observed networks. It also … campingplatz slowenien triglav nationalpark