[PDF] Top 20 Voter models on weighted networks
Has 10000 "Voter models on weighted networks" found on our website. Below are the top 20 most common "Voter models on weighted networks".
Voter models on weighted networks
... We study the dynamics of the voter and Moran processes running on top of complex network substrates where each edge has a weight depending on the degree of the nodes it connects. For each elementary dynamical step ... See full document
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Heterogenous mean-field analysis of a generalized voter-like model on networks
... of voter models in complex networks at the heterogeneous mean-field (HMF) level that (i) yields a unified picture for existing copy/invasion processes and (ii) allows for the introduction of further ... See full document
7
Recurrent Neural Networks as Weighted Language Recognizers
... based machine translation system should ex- tract the highest-weighted output string (i.e., the most likely translation) generated by an RNN, (Sutskever et al., 2014; Bahdanau et al., 2014). Currently this task is ... See full document
11
On metrics and models for multiplex networks
... multi-layer networks feature nontrivial dependencies among links of different ...and weighted multiplexes and validate their statistical significance against maximum-entropy null models that filter ... See full document
200
Feature Characterization in Some Weighted Directed Networks
... network models [1,2,3], since these models allow for the characterization of some structural properties which become fundamental for understanding the behavior of the ...social networks [4], biology ... See full document
5
Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality
... social networks of scientists in which the actors are authors of scientific papers, and a tie between two authors represents coauthorship of one or more ...The networks studied were based on publication ... See full document
7
Confidence in Structured Prediction Using Confidence Weighted Models
... In the past decade structured classification has seen much interest by the machine learning community. After the introduction of conditional random fields (CRFs) (Lafferty et al., 2001), and maximum mar- gin Markov ... See full document
11
Estimating topological properties of weighted networks from limited information.
... weights. A more recent approach [9,10] instead uses the limited topological information available on the network to generate an ensemble of graphs according to the configuration model (CM) [11], where the Lagrange ... See full document
5
Generalized voter-like models on heterogeneous networks
... simple models is that in reality individuals behave and relate to their peers in different ways, ...of voter-like models have been put forward, in an effort to take into account the intrinsic ... See full document
16
Perfect simulation of conditional and weighted models
... In this section we consider another perfect variant of Algorithm 4.9. In Section 4.5.3 it was seen that a realization of an area-interaction process can be obtained as a dependent thinning of a Poisson process. Dominated ... See full document
202
Reciprocity of weighted networks
... directed networks, reciprocal links have dramatic effects on dynamical processes, network growth, and higher-order structures such as motifs and ...binary networks has been extensively studied, that of ... See full document
9
The Politics of Voter Fraud
... of voter fraud ...of voter fraud in american elections ...studying voter fraud because government agencies fail to track it and are often unresponsive to information ...of voter fraud so that ... See full document
44
Weighted Additive DEA Models Associated with Dataset Standardization Techniques
... evaluation models will escape the harms resulting from the differences in orders of magnitude and units of measurement, which makes measure indicators be commensurable and play in the fair ...evaluation ... See full document
28
Some dynamic generalized information measures in the context of weighted models
... The weighted distributions arise naturally as a result of observations generated from a stochastic process and recorded with some weight ...of weighted distributions was introduced by Rao (1965) in ... See full document
14
Adaptively weighted group Lasso for semiparametric quantile regression models
... Assumption A4 and A4’ of Section 5. Under a strong sparsity condition, we establish selection consistency of AWG-Lasso when its weights, determined by some initial esti- mates, e.g., Lasso and group Lasso, obey a set of ... See full document
48
Distilling weighted finite automata from arbitrary probabilistic models
... In previous work, there have been various ap- proaches for estimating weighted automata. Meth- ods include state merging and weight estima- tion from a prefix tree data representation (Car- rasco and Oncina, 1994, ... See full document
11
Generalised exponentially weighted regression and dynamic Bayesian forecasting models
... replacing J by G . Average string lengths of the residuals incurred by the model (7.4.4), for 5 = -0.91 in case 1,5 = 0.30 in case 2 and < t > = 0.52 in case 3 are evaluated and tested for the Whiteness of the ... See full document
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THE VOTER JANUARY 2016
... Although this is the January 2016 edition of The Voter, it will be sent out before Christmas 2015. Therefore, it is not too late to wish each one of you a Happy Holiday, Merry Christmas, Happy Hanukkah, and a Very ... See full document
9
Voter Information Handbook
... As a Rhode Island voter, you have three options for safely and securely casting a ballot and this guide offers more information on each of these voting methods. I urge you to make your voice heard. If you have ... See full document
21
Networks and Neural Language Models
... neural networks, it is more common to avoid most uses of rich hand- derived features, instead building neural networks that take raw words as inputs and learn to induce features as part of the process of ... See full document
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