The Performance of Policy Networks: The Relation between Network Structure and Network Performance

2008 ◽  
Vol 36 (4) ◽  
pp. 497-524 ◽  
Author(s):  
Annica Sandström ◽  
Lars Carlsson
2018 ◽  
Vol 14 (10) ◽  
pp. 155014771880765
Author(s):  
He Li ◽  
Hongxi Yin ◽  
Shanshan Lin

In this article, a new optical network structure coping with network congestion is proposed, which is based on passive optical network, and adopts data storage devices coupled with optical line terminal to release network burden. It is shown by our network performance simulation that this network has many merits such as free-scale, fewer connections, larger clustering coefficient, and smaller average shortest path length in comparison to the passive optical network. The novel network structure can replace the far-end service connections with the near-end ones, reduce congestions in an optical network, and, furthermore, relieve traffic burden in optical backbone and metropolitan area networks.


2013 ◽  
Vol 03 (01) ◽  
pp. 187-195 ◽  
Author(s):  
Ziping Hu ◽  
Krishnaiyan Thulasiraman ◽  
Pramode K. Verma

Author(s):  
Zecong Ye ◽  
Zhiqiang Gao ◽  
Xiaolong Cui ◽  
Yaojie Wang ◽  
Nanliang Shan

AbstractIn image classification field, existing work tends to modify the network structure to obtain higher accuracy or faster speed. However, some studies have found that the neural network usually has texture bias effect, which means that the neural network is more sensitive to the texture information than the shape information. Based on such phenomenon, we propose a new way to improve network performance by making full use of gradient information. The dual features network (DuFeNet) is proposed in this paper. In DuFeNet, one sub-network is used to learn the information of gradient features, and the other is a traditional neural network with texture bias. The structure of DuFeNet is easy to implement in the original neural network structure. The experimental results clearly show that DuFeNet can achieve better accuracy in image classification and detection. It can increase the shape bias of the network adapted to human visual perception. Besides, DuFeNet can be used without modifying the structure of the original network at lower additional parameters cost.


2020 ◽  
Author(s):  
Jiyanbo Cao ◽  
Jinan Fiaidhi ◽  
Maolin Qi

This paper has reviewed the deep learning techniques which used in music generation. The research was based on <i>Sageev Oore's</i> proposed LSTM based recurrent neural network (Performance RNN). We have study the history of automatic music generation, and now we are using a state of the art techniques to achieve this mission. We have conclude the process of making a MIDI file to a structure as input of Performance RNN and the network structure of it.


2020 ◽  
Author(s):  
Jiyanbo Cao ◽  
Jinan Fiaidhi ◽  
Maolin Qi

This paper has reviewed the deep learning techniques which used in music generation. The research was based on <i>Sageev Oore's</i> proposed LSTM based recurrent neural network (Performance RNN). We have study the history of automatic music generation, and now we are using a state of the art techniques to achieve this mission. We have conclude the process of making a MIDI file to a structure as input of Performance RNN and the network structure of it.


2018 ◽  
Vol 32 (14) ◽  
pp. 1850174 ◽  
Author(s):  
Hui Zhang ◽  
Baiying Shi ◽  
Xiaohua Yu ◽  
Zhenhua Mou ◽  
Meiling Li ◽  
...  

Stability of urban subway systems is a crucial issue in daily operation. This paper proposes a node failing process to test the stability of subway network by structure-based and flow-based node evaluation indicators. Furthermore, three network evaluation indicators are used to measure the network performance. The average transfer number of times (ATT) that is strongly associated with network structure and passenger flow will be discussed specifically. The results show that removing nodes with large inbound passenger flow cannot effectively damage the subway network structure, but it can result in significant increment of the ATT in the whole network. Another finding is that the ATT is smaller in peak hours compared with off-peak hours.


2018 ◽  
Vol 10 (10) ◽  
pp. 3785 ◽  
Author(s):  
Jaana Korhonen ◽  
Alexandru Giurca ◽  
Maria Brockhaus ◽  
Anne Toppinen

To foster innovativeness for supporting (forest-based) bioeconomy development, participation in decision-making and interaction between diverse actors become a necessary precondition for designing and implementing transition policies. However, who forms the emerging policy networks, and which policy beliefs are promoted? Based on data from a national online survey, we performed a quantitative social network analysis to investigate emerging social structures and policy beliefs in the context of the Finnish forest-based bioeconomy. Our explorative analysis shows that research, governmental, and industrial organizations mainly constitute the Finnish forest-based bioeconomy network. Actors primarily exchange information, and most key organizations report high levels of trust among each other. However, the network structure is rather closed. This raises concerns about equal benefit sharing and the inclusiveness of concerned actors. We discuss the implication of this network structure for enabling new innovations. Finally, we present the key aspects and drivers of “business as usual”, and suggest an option for or a more transformative change in the Finnish forest-based bioeconomy.


2016 ◽  
Vol 83 (1) ◽  
pp. 200-222 ◽  
Author(s):  
Dorothee T.J.M. Peters ◽  
Erik Hans Klijn ◽  
Karien Stronks ◽  
Janneke Harting

Intersectoral policy networks may be effective in dealing with complex public health problems. Their performance is assumed to depend on network management and trust, as well as on integrated public health policy (i.e. policy coordination and integration). We studied the role of network management and trust in the realization of integrated public health policy and network performance, as well as the relation between integrated public health policy and network performance. In 34 Dutch local policy networks, we measured the perceptions of 278 actors through a Web-based survey and used regression analyses to assess the relations between policy variables. Management and trust were positively related to perceived integrated public health policy and network performance, while integrated public health policy was also positively related to perceived network performance. In public health, the performance of intersectoral policy networks may be improved by adequate network management, the creation of trust and policy coordination and integration. Future research could further explore the role of specific characteristics of the network manager, like the manager’s background, relation to the other actors and leadership style. Points for practitioners Regarding inter-sectoral policy networks in public health: first, when aiming for the realization of policy coordination and integration, the employment of network management strategies and the creation of trust are of importance for the network manager; and, second, when also aiming for the realization of network performance, the creation of policy coordination and integration is of additional importance for the network manager.


2020 ◽  
Author(s):  
Dennie Kim ◽  
Russell Funk ◽  
Aks Zaheer

Network perspectives in organizational research have focused primarily on how the embeddedness of actors shapes individual, or nodal, outcomes. Against this backdrop, a growing number of researchers have begun to adopt a wider lens on organizational networks, shifting the focus to collective, or whole network, performance. Yet, efforts to understand the relationship between whole network structure and whole network performance have produced conflicting findings, which suggests that a different approach may be needed. Drawing on macrostructural sociology, we propose a "whole network morphology" framework, which argues the whole network structure-performance relationship is contingent on other fundamental—relational and cultural—whole network dimensions. Subsequently, we undertake an application of our framework, through which we demonstrate how a morphological view helps address conflicting findings on the structure-performance relationship. Leveraging data on 350 million physician relationships, we study 250 whole networks known as Accountable Care Organizations (ACOs). Consistent with previous work, we do not find a clear association between structural connectedness and performance. However, we find that a more disconnected network structure is associated with negative ACO performance when the relational strength of network ties is high. We also find evidence of better ACO performance in the presence of a physician cultural orientation when the whole network is more connected.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yu Liu ◽  
Yong Wang ◽  
Haojin Qi ◽  
Xiaoming Ju

Most network pruning methods rely on rule-of-thumb for human experts to prune the unimportant channels. This is time-consuming and can lead to suboptimal pruning. In this paper, we propose an effective SuperPruner algorithm, which aims to find optimal pruned structure instead of pruning unimportant channels. We first train a VerifyNet, a kind of super network, which is able to roughly evaluate the performance of any given network structure. The particle swarm optimization algorithm is then used to search for optimal network structure. Lastly, the weights in the VerifyNet are used as the initial weights of the optimal pruned structure to make fine-tuning. VerifyNet is a network performance evaluation; our algorithm can quickly prune the network under any hardware constraints. Our algorithm can be applied in multiple fields such as object recognition and semantic segmentation. Extensive experiment results demonstrate the effectiveness of SuperPruner. For example, on CIFAR-10, the pruned VGG16 achieves 93.18% Top-1 accuracy and reduces 74.19% of FLOPs and 89.25% of parameters. Compared with state-of-the-art methods, our algorithm can achieve higher pruned ratio with less accuracy cost.


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