时态，单复数一致性，定冠词
摘要，实验用一般现在时
相关工作用过去式
Introduction
Some conventional community detection methods may have limited performance because
they merely focus on the networks’ topological structure
In order to compensate for the possible deficiencies of
apply
perform operates by
utilizing
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indicates
such assumption is not sufficient
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illustrate
demonstrate
wherereas
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Extensive expeperience conducted on a large dataset
motive
The concept of emotional intelligence (EI) has drawn a great amount of scholarly interest in recent years; however, attempts to measure individual differences in this ability remain controversial.
There is less research on the EI ability of Jordanian nurses, and the present study was undertaken to address this gap
介绍结构
The paper is structured as follows. In Sect.2we discuss the basic conceptsof information-theoretic bounded rationality, sampled-based interpretations ofbounded rationality in the context of Markov Chain Monte Carlo (MCMC),and the basic concepts of Variational Autoencoders. In Sect.3. we present theproposed decision-making model by combining sample-based decision-makingwith concurrent learning of priors parameterized by Variational Autoencoders.In Sect.4we evaluate the model with toy examples. In Sect.5we discuss ourresults.
贡献
Understanding the structure and analyzing properties of graphs are hence paramount to developing insights into the physical systems.
##方法
公式
, the expectation
the solution of s is given by the following set of equations
where A j = A ji = 1 when there is an edge between node i and j , and otherwise =0
where Xir
is defined as the propensity that node i belongs to community r.
utilizes
represents
Therefore, we can formulate another objective function as
X corresponds to the topological structure
We denote a density on X by p(X),
实验
Based on the models derived above, in this section, we introduce a simplified unified model that integrates topology as well
as content to conduct a pre-experiment about the mismatch effect
we designed the
following pre-experiment to illustrate the different influences of
semantic information with different trade-offs between topology
and content.
In the pre-experiment, we applied the unified model (5) to two real network datasets
take the following two steps in turns.
实验结果
We observe that HOPE, LLE and SDNE achieve high MAP values. Furthermore, HOPE can predict top 5 links with perfect accuracy.
A paper showcasing the results
to demonstrate our approach we evaluate two scenarios.
Our results indicate that using
to illustrate the differences in efficiency between the single prior agent andthe multi-prior agents, we plotted in Fig.4
Furthermore our results indicate that the multi-prior system generally outperforms the single-prior system in terms of utility.
We executed above initialization
with regard to the result of Facebook in
Fig. 1(b)
reflects the fact that
we can still observe
As shown in Fig. 2, for both ASCD-ARC and ASCD-NMI methods,the values of the objective function converge fast straight from the beginning and ASCD-ARC converges faster than ASCD-NMI
which are shown in Fig. 2
总结
In this study we ‘implemented bounded rational decision makers with adap-tive priors. We achieved this with Variational Autoencoder priors.
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