Topic modeling algorithms such as the latent Dirichlet allocation (LDA) play an important role in machine learning research. Fitting LDA using Gibbs sampler-related algorithms involves a sampling process over K topics...
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Local binary patterns was used to distinguish the Photorealistic Computer Graphics and Photographic Images, however the dimension of the extracted features is too high. Accordingly, the Local Ternary Count based on th...
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Publishing articles in high-impact English journals is difficult for scholars around the world, especially for non-native English-speaking scholars (NNESs), most of whom struggle with proficiency in English. In order ...
Intelligent Manufacturing has attracted global and continuous attention recent years, with more and more intelligent devices and systems applied in production. In this paper, we take China’s manufacturing listed firm...
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Intelligent Manufacturing has attracted global and continuous attention recent years, with more and more intelligent devices and systems applied in production. In this paper, we take China’s manufacturing listed firms to investigate the productivity difference between intelligent and general manufacturing firms. By the Cobb-Douglas production function, we built a Coefficient-varying Model and used Seemingly Unrelated Regression (SUR) to estimate the time-varying trend of productivity from 2011 to 2017. The empirical results show that “Intelligent Manufacturing” has obviously promoted the Labor factor utilization efficiency and the Total Factor Productivity (TFP) through the advances in technology. But it doesn’t have universally enhancing effect of all industries. The impact of “Intelligent Manufacturing” still remains to be observed overtime.
An important and widespread topic in cloud computing is text *** often use topic model which is a popular and effective technology to deal with related *** all the topic models,sLDA is acknowledged as a popular superv...
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ISBN:
(纸本)9781509012473
An important and widespread topic in cloud computing is text *** often use topic model which is a popular and effective technology to deal with related *** all the topic models,sLDA is acknowledged as a popular supervised topic model,which adds a response variable or category label with each document,so that the model can uncover the latent structure of a text dataset as well as retains the predictive power for supervised ***,sLDA needs to process all the documents at each iteration in the training *** the size of dataset increases to the volume that one node cannot deal with,sLDA will no longer be *** this paper we propose a novel model named *** which extends sLDA with stochastic variational inference(SVI) and *** can reduce the computational burden of sLDA and MapReduce extends the algorithm with *** makes the training become more efficient and the training method can be easily implemented in a large computer cluster or cloud *** results show that our approach has an efficient training process,and similar accuracy with sLDA.
This paper proposes a novel video face recognition method based on the convex hull model of kernel subspace sample selection. This method treats each video as an image set. Each image is represented as a point in the ...
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To overcome the drawbacks of traditional convex evidence, in this paper we proposed a modified convex evidence theory model, we presented the modified combination function and use it to combine mass function of ordere...
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ISBN:
(纸本)9781509045006
To overcome the drawbacks of traditional convex evidence, in this paper we proposed a modified convex evidence theory model, we presented the modified combination function and use it to combine mass function of ordered propositions, we present the calculation of the parameters of the proposed combination function, and proposed a more accurate method to find the proposition which is most likely true. The theoretical analysis and experimental results demonstrate that the proposed method has higher accuracy than traditional convex evidence.
Automatically analyzing interactions from video has gained much attention in recent years. Here a novel method has been proposed for analyzing interactions between two agents based on the tra jectories. Previous works...
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Automatically analyzing interactions from video has gained much attention in recent years. Here a novel method has been proposed for analyzing interactions between two agents based on the tra jectories. Previous works related to this topic are methods based on features, since they only extract features from objects. A method based on qualitative spatio-temporal relations is adopted which utilizes knowledge of the model(qualitative spatio-temporal relation calculi) instead of the original tra jectory information. Based on the previous qualitative spatio-temporal relation works, such as Qualitative tra jectory calculus(QTC), some new calculi are now proposed for long term and complex interactions. By the experiments, the results showed that our proposed calculi are very useful for representing interactions and improved the interaction learning more effectively.
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