In recent years, with the development of the Internet, it is more and more common for users to buy mobile phones on the Internet. On the one hand, sentiment analysis help customers to fully understand the performance ...
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In real life,a large amount of data describing the same learning task may be stored in different institutions(called participants),and these data cannot be shared among par-ticipants due to privacy *** case that diffe...
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In real life,a large amount of data describing the same learning task may be stored in different institutions(called participants),and these data cannot be shared among par-ticipants due to privacy *** case that different attributes/features of the same instance are stored in different institutions is called vertically distributed *** pur-pose of vertical‐federated feature selection(FS)is to reduce the feature dimension of vertical distributed data jointly without sharing local original data so that the feature subset obtained has the same or better performance as the original feature *** solve this problem,in the paper,an embedded vertical‐federated FS algorithm based on particle swarm optimisation(PSO‐EVFFS)is proposed by incorporating evolutionary FS into the SecureBoost framework for the first *** optimising both hyper‐parameters of the XGBoost model and feature subsets,PSO‐EVFFS can obtain a feature subset,which makes the XGBoost model more *** the same time,since different participants only share insensitive parameters such as model loss function,PSO‐EVFFS can effec-tively ensure the privacy of participants'***,an ensemble ranking strategy of feature importance based on the XGBoost tree model is developed to effectively remove irrelevant features on each ***,the proposed algorithm is applied to 10 test datasets and compared with three typical vertical‐federated learning frameworks and two variants of the proposed algorithm with different initialisation ***-mental results show that the proposed algorithm can significantly improve the classifi-cation performance of selected feature subsets while fully protecting the data privacy of all participants.
Topic modeling is a mainstream and effective technology to deal with text data, with wide applications in text analysis, natural language, personalized recommendation, computer vision, etc. Among all the known topic m...
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Topic modeling is a mainstream and effective technology to deal with text data, with wide applications in text analysis, natural language, personalized recommendation, computer vision, etc. Among all the known topic models, supervised Latent Dirichlet Allocation (sLDA) is acknowledged as a popular and competitive supervised topic model. How- ever, the gradual increase of the scale of datasets makes sLDA more and more inefficient and time-consuming, and limits its applications in a very narrow range. To solve it, a parallel online sLDA, named PO-sLDA (Parallel and Online sLDA), is proposed in this study. It uses the stochastic variational inference as the learning method to make the training procedure more rapid and efficient, and a parallel computing mechanism implemented via the MapReduce framework is proposed to promote the capacity of cloud computing and big data processing. The online training capacity supported by PO-sLDA expands the application scope of this approach, making it instrumental for real-life applications with high real-time demand. The validation using two datasets with different sizes shows that the proposed approach has the comparative accuracy as the sLDA and can efficiently accelerate the training procedure. Moreover, its good convergence and online training capacity make it lucrative for the large-scale text data analyzing and processing.
In the fields of social network analysis and knowledge graph, many semi-supervised learning algorithms based on graph convolutional neural network (GCN) have been widely used. Most of these algorithms usually improve ...
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The main purpose of this paper is to investigate the connection between the Painlev′e property and the integrability of polynomial dynamical systems. We show that if a polynomial dynamical system has Painlev′e prope...
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The main purpose of this paper is to investigate the connection between the Painlev′e property and the integrability of polynomial dynamical systems. We show that if a polynomial dynamical system has Painlev′e property, then it admits certain class of first integrals. We also present some relationships between the Painlev′e property and the structure of the differential Galois group of the corresponding variational equations along some complex integral curve.
Community mining has been the focus of many recent researches on dynamic social networks. In this paper, we propose a clustering based improved ant colony algorithm (CIACA) for community mining in social networks. The...
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作者:
LI YONG XU LUCollege of Mathematics
Key Laboratory of Symbolic computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012
In this paper, we study the persistence of lower dimensional tori for random Hamiltonian systems, which shows that majority of the unperturbed tori persist as Cantor fragments of lower dimensional ones under small per...
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In this paper, we study the persistence of lower dimensional tori for random Hamiltonian systems, which shows that majority of the unperturbed tori persist as Cantor fragments of lower dimensional ones under small perturbation. Using this result, we can describe the stability of the non-autonomous dynamic systems.
Image super-resolution is essential for a variety of applications such as medical imaging,surveillance imaging,and satellite imaging,among ***,the most popular color image super-resolution is performed in each color c...
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Image super-resolution is essential for a variety of applications such as medical imaging,surveillance imaging,and satellite imaging,among ***,the most popular color image super-resolution is performed in each color channel *** this paper,we show that the super-resolution quality can be further enhanced by exploiting the cross-channel *** by the High-Quality Linear Interpolation(HQLI)demosaicking algorithm by Malvar et al.,we design an image super-resolution scheme that integrates intra-channel interpolation with cross-channel details by isotropic linear *** its simplicity,our super-resolution method achieves the accuracy comparable with the existing fastest state-of-the-art super-resolution algorithm at 20 times faster *** is well applicable to applications that adopt traditional interpolations,for improved visual quality at trivial computation *** comparative study verifies the effectiveness and efficiency of the proposed super-resolution algorithm.
To satisfy the requirements of real-time and high quality mosaics, a bionic compound eye visual system was designed by simulating the visual mechanism of a fly compound eye. Several CCD cameras were used in this syste...
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To satisfy the requirements of real-time and high quality mosaics, a bionic compound eye visual system was designed by simulating the visual mechanism of a fly compound eye. Several CCD cameras were used in this system to imitate the small eyes of a compound eye. Based on the optical analysis of this system, a direct panoramic image mosaic algorithm was proposed. Several sub-images were collected by the bionic compound eye visual system, and then the system obtained the overlapping proportions of these sub-images and cut the overlap sections of the neighboring images. Thus, a panoramic image with a large field of view was directly mosaicked, which expanded the field and guaranteed the high resolution. The experimental results show that the time consumed by the direct mosaic algorithm is only 2.2% of that by the traditional image mosaic algorithm while guaranteeing mosaic quality. Furthermore, the proposed method effectively solved the problem of misalignment of the mosaic image and eliminated mosaic cracks as a result of the illumination factor and other factors. This method has better real-time properties compared to other methods.
With the rapid development of artificial intelligence, people have put forward higher requirements for robot path planning. As a more commonly used algorithm, reinforcement learning learns from experience by imitating...
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