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第37届中国控制会议

作者： Haibo Gu Peng Liu Xiong Wang Jinhu L LSC Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences Department of Automation University of Science and Technology of China School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Machine Intelligence Beihang University

Synchronization of directed complex networks has been extensively studied in the previous two decades due to its potential applications in the real world practices. To reveal and analyze the inherent mechanism of global synchronization in the complex networks with directed topologies, this paper attempts to developing a novel synchronization approach by using algebraic connectivity and PI control protocols. First, we studied the distributed PI control for synchronization in directed strongly connected networks and obtained some sufficient conditions to guarantee the networks reach global ***, a numerical example is given to verify the effectiveness of the proposed theoretical results.

关键词： Synchronization distributed PI control strongly connected network network control systems

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Global Pinning Synchronization with PI Controller in General Complex Directed Networks

Global Pinning Synchronization with PI Controller in General...

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第37届中国控制会议

作者： Peng Liu Haibo Gu Jinhu Lü Yu Kang Department of Automation University of Science and Technology of China LSC Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environmentand Beijing Advanced Innovation Center for Big Data and Brain Machine IntelligenceBeihang University

Global pinning synchronization in complex networks has been extensively studied in the last decades due to its potential *** question is how to design an available controller to achieve global synchronization when the network is *** we all know,the classical PI controller is most widely and successfully used in engineering systems with nonlinear ***,the global synchronization with PI controller in general complex directed networks still remain *** this paper we will theoretically show that the global synchronization of some directed networks can also be ensured by designing an appropriate PI controller and pioneering some selected nodes,then a simple numerical example will also be given to verify our main results.

关键词： Directed network Pining synchronization PI controller Lyapunov method

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Method of Age Estimation Based on ML-GMM Feature and Double Layers Estimation Model

Method of Age Estimation Based on ML-GMM Feature and Double ...

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作者： Min Hu Wendi Teng Yaona Zheng Keke Zhang AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information He Fei University of Technology

Feature extraction and estimation method are two key components of age estimation. This paper proposes a novel age estimation method based on Multi Levels Gaussian Mixture Model(MLGMM) and double layers estimation model. In the feature extraction phase, ML-GMM is used to construct different GMMs for different level features, which can well reflect the global and local age feature of facial images. In the estimation phase, double layers estimation model based on SVM-KNN is proposed. The first layer roughly divides age groups by using SVM. The second layer adopts KNN theory to find K images of consecutive age which have minimum sum of distance with the testing sample. The specific age is obtained by weighting these K age values. This paper performs a lot of experiments on mixed age database of FG-NET and MORPH-II databases. The mean absolute errors of age estimation are 3.22 years. Experimental results show that the proposed method is more effective than other methods of state-of-the-art for age estimation of facial images. It can extract more rich and complete age feature, improve the generalization ability of age estimation and reduce the mean absolute errors.

关键词： Multi Levels Gaussian Mixture Model SVM KNN Age Estimation

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A Fusion Decision Method Based on the Dynamic Fuzzy Density Assignment

A Fusion Decision Method Based on the Dynamic Fuzzy Density ...

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作者： Yanqiu Li Fuji Ren Min Hu Xiaohua Wang AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information He Fei University of Technology

Fuzzy density is an important part of fuzzy integral, which is used to describe the reliability of classifiers in the process of fusion. Most of the fuzzy density assignment methods are based on the training priori knowledge of the classifier and ignore the difference of the testing samples themselves. To better describe the real-time reliability of the classifier in the fusion process, the dispersion of the classifier is calculated according to the decision information which outputted by the classifier. Then the divisibility of the classifier is obtained through the information entropy of the dispersion. Finally, the divisibility and the priori knowledge are combined to get the fuzzy density which can be dynamically adjusted. Experiments on JAFFE and CK databases show that, compared with traditional fuzzy integral methods, the proposed method can effectively improve the decision performance of fuzzy integral and reduce the interference of unreliable output information to decision. And it is an effective multi-classifier fusion method.

关键词： Fuzzy Density Facial expression recognition (FER) Fuzzy integral Divisibility

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Three-dimensional tooth model reconstruction based on fusion of dental computed tomography images and laser-scanned images

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Shengwu Yixue Gongchengxue Zazhi/Journal of Biomedical Engineering 2017年第1期34卷 7-14页

作者： Zhang, Dongxia Gan, Yangzhou Xiong, Jing Xia, Zeyang Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences ShenzhenGuangdong518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology ShenzhenGuangdong518055 China

Complete three-dimensional (3D) tooth model provides essential information to assist orthodontists for diagnosis and treatment planning. Currently, 3D tooth model is mainly obtained by segmentation and reconstruction from dental computed tomography (CT) images. However, the accuracy of 3D tooth model reconstructed from dental CT images is low and not applicable for invisalign design. And another serious problem also occurs, i.e. frequentative dental CT scan during different intervals of orthodontic treatment often leads to radiation to the patients. Hence, this paper proposed a method to reconstruct tooth model based on fusion of dental CT images and laser-scanned images. A complete 3D tooth model was reconstructed with the registration and fusion between the root reconstructed from dental CT images and the crown reconstructed from laser-scanned images. The crown of the complete 3D tooth model reconstructed with the proposed method has higher accuracy. Moreover, in order to reconstruct complete 3D tooth model of each orthodontic treatment interval, only one pre-treatment CT scan is needed and in the orthodontic treatment process only the laser-scan is required. Therefore, radiation to the patients can be reduced significantly. Copyright © 2017 by Editorial Board of Journal of Biomedical Engineering.

关键词： Three dimensional computer graphics

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Latent embeddings for collective activity recognition

Latent embeddings for collective activity recognition

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IEEE Conference on advanced Video and Signal Based Surveillance (AVSS)

作者： Yongyi Tang Peizhen Zhang Jian-Fang Hu Wei-Shi Zheng Sun Yat-Sen University Guangzhou Guangdong CN School of Data and Computer Science Sun Yat-Sen University China The Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China

Rather than simply recognizing the action of a person individually, collective activity recognition aims to find out what a group of people is acting in a collective scene. Previous state-of-the-art methods using hand-crafted potentials in conventional graphical model which can only define a limited range of relations. Thus, the complex structural dependencies among individuals involved in a collective scenario cannot be fully modeled. In this paper, we overcome these limitations by embedding latent variables into feature space and learning the feature mapping functions in a deep learning framework. The embeddings of latent variables build a global relation containing person-group interactions and richer contextual information by jointly modeling broader range of individuals. Besides, we assemble attention mechanism during embedding for achieving more compact representations. We evaluate our method on three collective activity datasets, where we contribute a much larger dataset in this work. The proposed model has achieved clearly better performance as compared to the state-of-the-art methods in our experiments.

关键词： Feature extraction Activity recognition Sun Graphical models machine learning Legged locomotion Visualization

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Online hashing

arXiv

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arXiv 2017年

作者： Huang, Long-Kai Yang, Qiang Zheng, Wei-Shi School of Data and Computer Science Sun Yat-sen University Guangzhou510275 China School of Computer Science and Engineering Nanyang Technological University Singapre Singapore Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education

Although hash function learning algorithms have achieved great success in recent years, most existing hash models are off-line, which are not suitable for processing sequential or online data. To address this problem, this work proposes an online hash model to accommodate data coming in stream for online learning. Specifically, a new loss function is proposed to measure the similarity loss between a pair of data samples in hamming space. Then, a structured hash model is derived and optimized in a passive-aggressive way. Theoretical analysis on the upper bound of the cumulative loss for the proposed online hash model is provided. Furthermore, we extend our online hashing from a single-model to a multi-model online hashing that trains multiple models so as to retain diverse online hashing models in order to avoid biased update. The competitive efficiency and effectiveness of the proposed online hash models are verified through extensive experiments on several large-scale datasets as compared to related hashing methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Hash functions

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Point of interest recommendation with social and geographical influence 4

Point of interest recommendation with social and geographica...

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4th IEEE International Conference on Big Data, Big Data 2016

作者： Zhang, Da-Chuan Li, Mei Wang, Chang-Dong School of Data and Computer Science Sun Yat-sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China

ISBN: (纸本)9781467390040

Point of interest (POI) recommendation, a service which can help people discover useful and interesting locations has emerged rapidly with the development of location-based social networks (LBSNs), like Foursquare, Gowalla and Wechat. The large number of check-in histories make it possible to mine the preference of each user and then to provide accurate personalized POI recommendation. In real-world applications, apart from check-in data, there are some other useful information available for making better POI recommendation, such as social relationship among users and geographical influence. In this paper, a new POI recommendation method called Social and Geographical Fusing Model (SGFM) is designed. The basic idea is summarized as follows. Firstly, the users' check-in records and social influence are integrated in a combinative model. Then the global user impact factors generated by the PageRank algorithm are used to improve the combinative model. Secondly, a geographical influence measurement is used to capture the users' physical check-in characters. Finally, the enhanced combinative model and geographical influence are combined together to form a new framework. Extensive experiments have been conducted on a famous dataset, namely Gowalla. The comparison results confirm that the proposed framework outperforms state-of-the-art POI recommendation methods significantly. © 2016 IEEE.

关键词： Collaborative filtering

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Generative adversarial network for abstractive text summarization

arXiv

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arXiv 2017年

作者： Liu, Linqing Lu, Yao Yang, Min Qu, Qiang Zhu, Jia Li, Hongyan Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Alberta Machine Intelligence Institute School of Computer Science South China Normal University Moe Key Laboratory of Machine Perception Peking University

In this paper, we propose an adversarial process for abstrac-tive text summarization, in which we simultaneously train a generative model G and a discriminative model D. In par-ticular, we build the generator G as an agent of reinforce-ment learning, which takes the raw text as input and predicts the abstractive summarization. We also build a discriminator which attempts to distinguish the generated summary from the ground truth summary. Extensive experiments demon-strate that our model achieves competitive ROUGE scores with the state-of-the-art methods on CNN/Daily Mail dataset. Qualitatively, we show that our model is able to generate more abstractive, readable and diverse summaries1. Copyright © 2017, The Authors. All rights reserved.

关键词： Text processing

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Capability of local operations and classical communication to distinguish bipartite unitary operations

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Physical Review A 2017年第5期96卷 052327-052327页

作者： Lvzhou Li Shenggen Zheng Haozhen Situ Daowen Qiu Institute of Computer Science Theory School of Data and Computer Science Sun Yat-Sen University Guangzhou 510006 China The Key Laboratory of Machine Intelligence and Advanced Computing (Sun Yat-Sen University) Ministry of Education Guangzhou 510006 China College of Mathematics and Informatics South China Agricultural University Guangzhou 510642 China

The problem studied in this paper is, if the number of queries to unitary operations is fixed, say k, then when do local operations and classical communication (LOCC) suffice for optimally distinguishing bipartite unitary operations? We consider the above problem for two-qubit unitary operations in the case of k=1, showing that for two two-qubit entangling unitary operations without local parties, LOCC achieves the same distinguishability as the global operations. Specifically, we obtain the following: (i) if such two unitary operations are perfectly distinguishable by global operations, then they are perfectly distinguishable by LOCC also, and (ii) if they are not perfectly distinguishable by global operations, then LOCC can achieve the same optimal discrimination probability as the global operations.

关键词： Quantum gates Resource theories

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