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32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019

作者： Lv, Kai Du, Heming Hou, Yunzhong Deng, Weijian Sheng, Hao Jiao, Jianbin Zheng, Liang Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University University of Chinese Academy of Sciences Australian National University

ISBN: (纸本)9781728125060

This paper focuses on the problem of vehicle re-identification (Re-ID). In our attempt, we propose a re-identification framework by exploiting vehicle location and time stamps. The location and time information have the potential to cover the shortage of appearance-based feature representations. First, we introduce an ensemble technique to combine the informative cues of multiple Re-ID models effectively. To further improve the accuracy, we then build up a system to acquire the vehicle location and time stamps. Specifically, we utilize the detected results to obtain the needed information. With the help of the proposed system, we can remove irrelevant images from a given ranking list. Our system finished 3rd place in the 2019 AI-City challenge for city-scale multi-camera vehicle re-identification. © 2019 IEEE Computer Society. All rights reserved.

关键词： Vehicles

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On the Detection of Shilling Attacks in Federated Collaborative Filtering

On the Detection of Shilling Attacks in Federated Collaborat...

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Reliable Distributed Systems

作者： Yangfan Jiang Yipeng Zhou Di Wu Chao Li Yan Wang School of Data and Computer Science Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing (Sun Yat-sen University) Ministry of Education China Macquarie University Sydney NSW Australia Tencent Inc Shenzhen China

ISBN: (数字)9781728176260

ISBN: (纸本)9781728176277

Federated collaborative filtering (Fed-CF) is a variant of federated learning (FL) models, which can protect user privacy in recommender systems. In Fed-CF, the recommendation model is collectively trained across multiple decentralized clients by exchanging gradients only. However, the decentralized nature of Fed-CF makes it vulnerable to shilling attacks, which can be realized by inserting fake ratings of target items to distort recommendation results. Unfortunately, previous detection algorithms cannot work well in the FL framework, as all original data samples are not disclosed at all. In this paper, we are the first to systematically study the problem of shilling attacks in the context of federated learning, and propose an effective detection method called Federated Shilling Attack Detector (FSAD) to detect shilling attackers in Fed-CF. We first show the feasibility of shilling attacks in Fed-CF. Next, we dedicatedly design four novel features based on exchanged gradients among clients. By incorporating these gradient-based features, we train a semi-supervised Bayes classifier to identify shilling attackers effectively. Finally, we conduct extensive experiments based on real-world datasets to evaluate the performance of our proposed FSAD method. The experimental results show that FSAD can detect shilling attackers in Fed-CF with high accuracy, with the F 1 value as high as 0.90 on the Netflix dataset, which approaches the performance of the optimal detector that utilizes complete private user information for detection.

关键词： Privacy Collaborative filtering Detectors Collaborative work Information filters Reliability Recommender systems

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Signal approximation with Pascal’s triangle and sampling

Signal approximation with Pascal’s triangle and sampling

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Chinese Control and Decision Conference, CCDC

作者： Lei Chen Xinghuo Yu Jinhu Lü School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China School of Engineering RMIT University Melbourne VIC Australia

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

This brief explores the approximation properties of a unique basis expansion based on Pascal's triangle, which realizes a sampled-data driven approach between a continuous-time signal and its discrete-time representation. The roles of certain parameters, such as sampling time interval or model order, and signal characteristics, i.e., its curvature, on the approximation are investigated. Approximate errors in one and multiple-step predictions are analyzed. Furthermore, time-variant approximations under the thresholds of signal curvature are employed to narrow errors and provide flexibilities.

关键词： Shape Electronic mail Analytical models Mathematical analysis data models Upper bound

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A Distributed Privacy-Preserving Learning Dynamics in General Social Networks

arXiv

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arXiv 2020年

作者： Tao, Youming Chen, Shuzhen Li, Feng Yu, Dongxiao Yu, Jiguo Sheng, Hao School of Computer Science and Technology Shandong University Qingdao266237 China Big Data Institute Qilu University of Technology Jinan250353 China State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

In this paper, we study a distributed privacy-preserving learning problem in social networks with general topology. The agents can communicate with each other over the network, which may result in privacy disclosure, since the trustworthiness of the agents cannot be guaranteed. Given a set of options which yield unknown stochastic rewards, each agent is required to learn the best one, aiming at maximizing the resulting expected average cumulative reward. To serve the above goal, we propose a four-staged distributed algorithm which efficiently exploits the collaboration among the agents while preserving the local privacy for each of them. In particular, our algorithm proceeds iteratively, and in every round, each agent i) randomly perturbs its adoption for the privacy-preserving purpose, ii) disseminates the perturbed adoption over the social network in a nearly uniform manner through random walking, iii) selects an option by referring to the perturbed suggestions received from its peers, and iv) decides whether or not to adopt the selected option as preference according to its latest reward feedback. Through solid theoretical analysis, we quantify the trade-off among the number of agents (or communication overhead), privacy preserving and learning utility. We also perform extensive simulations to verify the efficacy of our proposed social learning algorithm. Copyright © 2020, The Authors. All rights reserved.

关键词： Iterative methods

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A Combined Guidance Law for Intercepting Hypersonic Large Maneuvering Targets

A Combined Guidance Law for Intercepting Hypersonic Large Ma...

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Chinese Automation Congress (CAC)

作者： Bingqian Zhao Xiwang Dong Qingdong Li Zhang Ren Science and Technology on Aircraft Control Laboratory School of Automation Science and Electronic Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing School of Automation Science and Electronic Engineering Beihang University Beijing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

This paper proposes a combined guidance law based on differential geometry and true proportional guidance (TPN). Due to the increase of the interceptor acceleration component perpendicular to the speed direction, the line-of- sight angular rate can be converged quickly, and the convergence rate of the miss distance is faster than that of TPN. Therefore, the combined guidance law can intercept the target in a short time, reducing the possibility of target escape. This paper gives a numerical simulation example under the two conditions of large maneuvering and snake maneuvering of the target, both of which achieve effective interception of the target. Therefore, the designed combined guidance law is effective for intercepting hypersonic large maneuvering targets.

关键词： Angular velocity Geometry Acceleration Mathematical model Aircraft navigation Technological innovation Trajectory

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Collusion-Proof Result Inference in Crowdsourcing

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Journal of Computer Science & Technology 2018年第2期33卷 351-365页

作者： Peng-Peng Chen Hai-Long Sun Yi-Li Fang Jin-Peng Huai State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing 100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing 100191 China

In traditional crowdsourcing, workers are expected to provide independent answers to tasks so as to ensure the diversity of answers. However, recent studies show that the crowd is not a collection of independent workers, but instead that workers communicate and collaborate with each other. To pursue more rewards with little effort, some workers may collude to provide repeated answers, which will damage the quality of the aggregated results. Nonetheless, there are few efforts considering the negative impact of collusion on result inference in crowdsourcing. In this paper, we are specially concerned with the Collusion-Proof result inference problem for general crowdsourcing tasks in public platforms. To that end, we design a metric, the worker performance change rate, to identify the colluded answers by computing the difference of the mean worker performance before and after removing the repeated answers. Then we incorporate the collusion detection result into existing result inference methods to guarantee the quality of the aggregated results even with the occurrence of collusion behaviors. With real-world and synthetic datasets, we conducted an extensive set of evaluations of our approach. The experimental results demonstrate the superiority of our approach in comparison with the state-of-the-art methods.

关键词： crowdsourcing quality control collusion collaborative crowdsourcing result inference

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Time-varying formation tracking control for UAV-UGV heterogeneous swarm systems with switching directed topologies

Time-varying formation tracking control for UAV-UGV heteroge...

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International Conference on Control and Automation (ICCA)

作者： Siquan Zhou Xiwang Dong Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing P.R. China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing P.R. China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

This paper studies time-varying formation tracking control problems for UAV-UGV heterogeneous swarm systems. The UAVs and UGVs need to achieve the desired time-varying formation and track the reference trajectory of a leader synchronously under switching directed topologies. Firstly, the cooperative control model for UAV-UGV heterogeneous swarm system is established by using algebraic graph theory. Then, the formation tracking control protocol based on a distributed observer is designed and the convergence is proved by using piecewise Lyapunov theory. Furthermore, the feasible conditions to achieve the time-varying formation tracking are analyzed, and the algorithm to select the control parameters is proposed. Finally, a numerical simulation example is provided to demonstrate the effectiveness of the proposed control approach.

关键词： Topology Switches Time-varying systems Observers Radar tracking Manganese Control systems

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Finite-Time Time-Varying Group Formation Tracking for High-Order Multi-Agent Systems with Mismatched Disturbances under Directed Graphs

Finite-Time Time-Varying Group Formation Tracking for High-O...

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International Conference on Control and Automation (ICCA)

作者： Lei Tian Yongzhao Hua Xiwang Dong Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing P.R. China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing P.R. China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

Finite-time time-varying group formation (FT-TVGF) tracking control problems for high-order multi-agent systems (MASs) are studied in this paper. Different from previous work, the approaches proposed in this paper combine group formation tracking control with finite-time control, not only that, the agents in each group can achieve time-varying sub-formations and the relative configuration between different groups can be adjusted simultaneously. First, all agents are divided into three types, including the virtual leader, the group leader, and the follower. The virtual leader is added to plan the trajectory of MASs. Subgroups can be interacted with each other by the communication among group leaders. Followers achieve the finite-time formation tracking of group leaders. Then the disturbance observer is constructed to estimate the mismatched disturbances of all group leaders and followers in finite time. Furthermore, based on finite time control theory and observer theory, a distributed control protocol is presented to make MASs realize FT-TVGF tracking under directed graph. The proof of close-loop stability of MASs is accomplished using Lyapunov theory. Finally, numerical simulations verify the theoretical analysis of this paper.

关键词： Disturbance observers Trajectory Tracking Protocols Directed graphs Technological innovation Multi-agent systems

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Self-to-self transitions in open quantum systems:the origin and solutions

Self-to-self transitions in open quantum systems:the origin ...

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第三十九届中国控制会议

作者： Fang Gao Yaoxiong Wang Qing Gao Dewen Cao Feng Shuang College of Electrical Engineering Guangxi University Institute of Intelligent Machines Chinese Academy of Sciences School of Automation Science and Electrical Engineering Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University University Key Laboratory of Intelligent Perception and Computing of Anhui Province Anqing Normal University

The information of quantum pathways can be extracted in the framework of the Hamiltonianencoding and Observable-decoding *** closed quantum systems,only off-diagonal elements of the Hamiltonian in the Hilbert space is required to be encoded to obtain the desired *** open quantum systems,environment-related terms will appear in the diagonal elements of the Hamiltonian in the Liouville *** diagonal encodings have to be performed to differentiate different pathways,which will lead to self-to-self transitions and inconsistency of pathway amplitudes with Dyson *** this work,a well-designed transformation is proposed to avoid the counterintuitive transitions and the inconsistency,with or without control *** simulations show that the method are consistent with Dyson expansion.

关键词： Self-to-self transitions in open quantum systems:the origin and solutions origin

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Crowd Counting for Static Images: A Survey of Methodology

Crowd Counting for Static Images: A Survey of Methodology

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第三十九届中国控制会议

作者： Ying Luo Jinhu Lu Baochang Zhang School of Automation Science and Electrical Engineering Beihang University Shenyuan Honors College Beihang University School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environmentand Beijing Advanced Innovation Center for Big Data and Brain ComputingBeihang University

Crowd counting for static images is one of the typical application fields of image processing. it is essential to direct crowd analysis for public security purposes under the background of a rapidly growing social environment. Crowd counting for static images involves crucial challenges such as occlusions, scale variations, scene perspective distortions and diverse crowd distributions. It has now become an independent research hotspot. This paper investigates the literature of crowd counting tasks, summarizes the evolution of counting approaches, compares and analyzes traditional methods and current trends of CNN estimation-based counting, and then evaluates common datasets for crowd counting tasks. Conclusions concerning summarizations and prospects are made.

关键词： Crowd counting crowd analysis pattern recognition computer vision

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