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arXiv 2021年

作者： Yin, Hoover H.F. Ng, Ka Hei Zhong, Allen Z. Yeung, Raymond W. Yang, Shenghao Chan, Ian Y.Y. The N-hop Technologies Limited Hong Kong The Institute of Network Coding The Chinese University of Hong Kong Hong Kong The Department of Information Engineering The Chinese University of Hong Kong Hong Kong Limited The Department of Physics The Chinese University of Hong Kong Hong Kong The Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong The School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Key Laboratory of IoT Intelligent Systems and Wireless Network Technology Shenzhen Research Institute of Big Data Shenzhen China The Department of Economics The Chinese University of Hong Kong Hong Kong

Batched network coding (BNC) is a low-complexity solution to network transmission in multi-hop packet networks with packet loss. BNC encodes the source data into batches of packets. As a network coding scheme, the intermediate nodes perform recoding on the received packets belonging to the same batch instead of just forwarding them. A recoding scheme that may generate more recoded packets for batches of a higher rank is also called adaptive recoding. Meanwhile, in order to combat burst packet loss, the transmission of a block of batches can be interleaved. Stream interleaving studied in literature achieves the maximum separation among any two consecutive packets of a batch, but permutes packets across blocks and hence cannot bound the buffer size and the latency. To resolve the issue of stream interleaver, we design an intrablock interleaver for adaptive recoding that can preserve the advantages of using a block interleaver when the number of recoded packets is the same for all batches. We use potential energy in classical mechanics to measure the performance of an interleaver, and propose an algorithm to optimize the interleaver with this performance measure. Our problem formulation and algorithm for intrablock interleaving are also of independent interest. © 2021, CC BY-NC-ND.

关键词： network coding

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Deep learning for depression recognition with audiovisual cues: A review

arXiv

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arXiv 2021年

作者： He, Lang Niu, Mingyue Tiwari, Prayag Marttinen, Pekka Su, Rui Jiang, Jiewei Guo, Chenguang Wang, Hongyu Ding, Songtao Wang, Zhongmin Pan, Xiaoying Dang, Wei School of Computer Science and Technology Xi'an University of Posts and Telecommunications Shaanxi Xi'an710121 China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications Shaanxi Xi'an710121 China Beijing100190 China Beijing100049 China Department of Computer Science Aalto University Espoo Finland School of Foreign Languages Northwest University Shaanxi Xi'an China School of Electronic Engineering Xi'an University of Posts and Telecommunications Xi'an China School of Electronics and Information Northwestern Polytechnical University Shaanxi Xi'an China Shaanxi Mental Health Center Shaanxi Xi'an710061 China

With the acceleration of the pace of work and life, people have to face more and more pressure, which increases the possibility of suffering from depression. However, many patients may fail to get a timely diagnosis due to the serious imbalance in the doctor-patient ratio in the world. Promisingly, physiological and psychological studies have indicated some differences in speech and facial expression between patients with depression and healthy individuals. Consequently, to improve current medical care, many scholars have used deep learning to extract a representation of depression cues in audio and video for automatic depression detection. To sort out and summarize these works, this review introduces the databases and describes objective markers for automatic depression estimation (ADE). Furthermore, we review the deep learning methods for automatic depression detection to extract the representation of depression from audio and video. Finally, this paper discusses challenges and promising directions related to automatic diagnosing of depression using deep learning technologies. © 2021, CC BY.

关键词： Diagnosis

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Robust visual tracking via combinative deep learning

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Journal of Physics: Conference Series 2018年第1期1074卷

作者： Jia Wen JiWei Zhao PengFei Liu Hongjun Wang The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao P.R.China Information Science and Engineering College Yanshan University Qinhuangdao P.R.China State Key Laboratory of Software Engineering of Hebei Province Yanshan University Qinhuangdao P.R.China

Object tracking is a hot topic in computer vision. In recent years, a large number of trackers has been proposed, in which the deep learning tracker has achieved excellent performance. The real-time capability of the deep learning tracker is not good enough due to the high-complexity of the network structures. This paper proposed an innovative tracking method to solve this problem. There are three important differences between this tracker and the other deep learning trackers. Firstly, the overcomplete basis in the deep learning tracker results in heavy computational cost. In order to reduce the complexity of the network, fewer units are used in the first hidden layer to replace the overcomplete basis. Secondly, a training method combining two observation models is used in the tracking process. The denoising automatic encoder is used in the first layer and the backpropagation is used in the other layers. This can avoid the diffusion of gradients which is caused by BP and adapt to the change of the targets easier. Thirdly, this tracker using adaptive particle filter to track targets. The number of particles is dynamic changes in tracking process. In this paper, we use different kinds of unlabelled datum to train network and initialize observation model. The observation model uses the samples collected in the tracking to adjust dynamically so as to adapt to the target appearance and complex environment. Compared with the existing methods, the results of experiments in different video sequences show that this tracker has a higher speed and the similar accuracy compared.

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An approach for security evaluation and certification of a complete quantum communication system

arXiv

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arXiv 2019年

作者： Sajeed, Shihan Chaiwongkhot, Poompong Huang, Anqi Qin, Hao Egorov, Vladimir Kozubov, Anton Gaidash, Andrei Chistiakov, Vladimir Vasiliev, Artur Gleim, Artur Makarov, Vadim Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering University of Toronto M5S 3G4 Canada Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China CAS Quantum Network Co. Ltd. 99 Xiupu road Shanghai201315 China Faculty of Photonics and Optical Information ITMO University Kadetskaya line 3/2 St. Petersburg199034 Russia Shanghai Branch National Laboratory for Physical Sciences at Microscale CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai201315 China

Although quantum communication systems are being deployed on a global scale, their realistic security certification is not yet available. Here we present a security evaluation and improvement protocol for complete quantum communication systems. The protocol subdivides a system by defining seven system implementation sub-layers based on a hierarchical order of information flow;then it categorises the known system implementation imperfections by hardness of protection and practical risk. Next, an initial analysis report lists all potential loopholes in its quantum-optical part. It is followed by interactions with the system manufacturer, testing and patching most loopholes, and re-assessing their status. Our protocol has been applied on multiple commercial quantum key distribution systems to improve their security. A detailed description of our methodology is presented with the example of a subcarrier-wave system. Our protocol is a step towards future security evaluation and security certification standards. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum communication

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Transferring knowledge distillation for multilingual social event detection

arXiv

引用

arXiv 2021年

作者： Ren, Jiaqian Peng, Hao Jiang, Lei Wu, Jia Tong, Yongxin Wang, Lihong Bai, Xu Wang, Bo Yang, Qiang Institute of Information Engineering Chinese Academy of Sciences The School of Cyber Security University of Chinese Academy of Sciences Beijing100041 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China The School of Cyber Science and Technology Beihang University Beijing100083 China Institute of Information Engineering Chinese Academy of Sciences Beijing100041 China The Department of Computing Macquarie University Sydney Australia The State Key Laboratory of Software Development Environment The School of Computer Science and Engineering Beihang University Beijing100083 China The National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100029 China The Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong AI Group WeBank Co. Ltd. China

Recently published graph neural networks (GNNs) show promising performance at social event detection tasks. However, most studies are oriented toward monolingual data in languages with abundant training samples. This has left the more common multilingual settings and lesser-spoken languages relatively unexplored. Thus, we present a GNN that incorporates cross-lingual word embeddings for detecting events in multilingual data streams. The first exploit is to make the GNN work with multilingual data. For this, we outline a construction strategy that aligns messages in different languages at both the node and semantic levels. Relationships between messages are established by merging entities that are the same but are referred to in different languages. Non-English message representations are converted into English semantic space via the cross-lingual word embeddings. The resulting message graph is then uniformly encoded by a GNN model. In special cases where a lesser-spoken language needs to be detected, a novel cross-lingual knowledge distillation framework, called CLKD, exploits prior knowledge learned from similar threads in English to make up for the paucity of annotated data. Experiments on both synthetic and real-world datasets show the framework to be highly effective at detection in both multilingual data and in languages where training samples are scarce. © 2021, CC BY.

关键词： Embeddings

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A Systematic Literature Review of Robust Federated Learning: Issues, Solutions, and Future Research Directions

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ACM Computing Surveys 1000年

作者： Md Palash Uddin Yong Xiang Mahmudul Hasan Jun Bai Yao Zhao Longxiang Gao School of Information Technology Deakin University Burwood Australia Deakin University Burwood Australia Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Shandong Academy of Sciences Qilu University of Technology Jinan China Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China

Federated Learning (FL) has emerged as a promising paradigm for training machine learning models across distributed devices while preserving their data privacy. However, the robustness of FL models against adversarial data and model attacks, noisy updates, and label-flipped data issues remain a critical concern. In this paper, we present a systematic literature review using the PRISMA framework to comprehensively analyze existing research on robust FL. Through a rigorous selection process using six key databases (ACM Digital Library, IEEE Xplore, ScienceDirect, Springer, Web of Science, and Scopus), we identify and categorize 244 studies into eight themes of ensuring robustness in FL: objective regularization, optimizer modification, differential privacy employment, additional dataset requirement and decentralization orchestration, manifold, client selection, new aggregation algorithms, and aggregation hyperparameter tuning. We synthesize the findings from these themes, highlighting the various approaches and their potential gaps proposed to enhance the robustness of FL models. Furthermore, we discuss future research directions, focusing on the potential of hybrid approaches, ensemble techniques, and adaptive mechanisms for addressing the challenges associated with robust FL. This review not only provides a comprehensive overview of the state-of-the-art in robust FL but also serves as a roadmap for researchers and practitioners seeking to advance the field and develop more robust and resilient FL systems.

关键词： Federated Learning Robustness Attack Countermeasure Defence.

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DEFECT INSPECTION FOR STRUCTURAL TEXTURE SURFACE BASED ON GENERALIZED LOW-RANK APPROXIMATIONS OF MATRICES

DEFECT INSPECTION FOR STRUCTURAL TEXTURE SURFACE BASED ON GE...

引用

International Symposium on Intelligent Signal Processing and Communication Systems

作者： Yan-Xing Wang Yi-Gang Cen Lie-Quan Liang Ming Zeng Vladimir Mladenovic Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing School of Computer and Information Technology Beijing Jiaotong University Beijing Guangdong key laboratories on e-commerce market application technology Guangdong university of finance and economics Guangzhou China School of Automation Science and Engineering South China University of Technology Guangzhou China Faculty of Technical Sciences Cacak University of Kragujevac Cacak Serbia

In this paper, we propose an automated surface inspection approach based on generalized low-rank approximations of matrices(GLRAM). The GLRAM uses a series of low-rank matrices to approximate the structural texture backgrounds of the original defective images. Then the difference images obtained by the original defective images and the low-rank approximations will retain the defect areas. Finally, we can easily segment the defect area from the original image using a simple threshold segmentation method. Experimental results show that our proposed method can extract defect areas well from the structurally textured image.

关键词： Defect inspection Structural textures Machine vision Generalized low-rank approximations of matrices

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Independent component analysis based on information bottleneck

Abstract and Applied Analysis

引用

Abstract and Applied Analysis 2015年第none期2015卷 1-8页

作者： Ke, Qiao Zhang, Jiangshe Srivastava, H.M. Wei, Wei Chen, Guang-Sheng School of Mathematics and Statistics Xi'An Jiaotong University Xi'an 710049 China Department of Mathematics and Statistics University of Victoria Victoria V8W3R4 BC Canada School of Computer Science and Engineering Xi'An University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an 710048 China Department of Construction and Information Engineering Guangxi Modern Vocational Technology College Hechi Guangxi 547000 China

The paper is mainly used to provide the equivalence of two algorithms of independent component analysis (ICA) based on the information bottleneck (IB). In the viewpoint of information theory, we attempt to explain the two classical algorithms of ICA by information bottleneck. Furthermore, via the numerical experiments with the synthetic data, sonic data, and image, ICA is proved to be an edificatory way to solve BSS successfully relying on the information theory. Finally, two realistic numerical experiments are conducted via FastICA in order to illustrate the efficiency and practicality of the algorithm as well as the drawbacks in the process of the recovery images the mixing images. © 2015 Qiao Ke et al.

关键词： INDEPENDENT component analysis ALGORITHMS information theory IMAGE processing NUMERICAL analysis

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Package of the vector math library based on the sunway processor

引用

Ruan Jian Xue Bao/Journal of Software 2014年 25卷 70-79页

作者： Xie, Qing-Chun Zhang, Yun-Quan Li, Yan Pang, Ren-Bo Wu, Zai-Long Lu, Yong-Quan Gao, Peng-Dong High Performance Computing Center Communication University of China Beijing100024 China Laboratory of Parallel Computing Institute of Software The Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Computer Architecture Institute of Computing Technology The Chinese Academy of Sciences Beijing100190 China Department of Computer and Network National Marine Environmental Forecasting Center Beijing100081 China School of Information Sceience and Technology The Ocean University of China Qingdao266100 China

This paper first introduces the SIMD (single instruction multiple data) extension technology and presents three ways to use SIMD instructions. It is considered that calling the third party library, which is optimized for the target platform by using those instructions, is the best way to benefit the developers. Next, it introduces the China-developed SW-1600 CPU, and a software package called SW-VML, which consists of many mathematical functions, by using the SIMD extension technology. In order to solve the additional overhead caused by unaligned address access and transformation between vector and scalar array, the paper provides some performance optimized methods, such as aligned address access, simplifying vector condition branch and loop unrolling. An upgrade to SW-VML is also offered to support multi-thread with OpenMP. Finally, functions in the package are tested using arrays of different sizes on SW-1600, and the test results show that high performance is achieved with the technology of the SIMD vectorization. Compared with the traditional methods of the scalar calculation, the average speedup is up to 2.06. The performance speedup of package using 4 threads is up to 2.26 compared to using a single thread. SW-VML is a common vector function package for domestic Sunway processor series, and it can be used as a basic toolkit which is beneficial to high performance computing on Sunway platform. ©2014 ISCAS.

关键词： Vectors

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Cooperative Multi-source Data Trading

Cooperative Multi-source Data Trading

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Jin Cheng Ningning Ding John C. S. Lui Jianwei Huang School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Shenzhen Data Science and Analytics Thrust Information Hub Hong Kong University of Science and Technology Guangzhou Department of Computer Science and Engineering The Chinese University of Hong Kong School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen Key Laboratory of Crowd Intelligence Empowered Low-Carbon Energy Network and CSIJRI Joint Research Centre on Smart Energy Storage The Chinese University of Hong Kong Shenzhen

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In the era of big data, data trading significantly enhances data-driven technologies by facilitating data sharing. Despite the clear advantages often experienced by data users when incorporating multiple sources, the topic of multi-source data trading remains largely unexplored. This paper designs a novel data trading framework, which enables multi-source data trading through multi-source cooperation. The proposed framework aims to improve data usage efficiency and increase seller revenue. In particular, we model data sellers’ cooperative decisions through the Nash bargaining framework and systematically outline the interactions between sellers and buyers as a two-stage Stackelberg game. A key contribution of this work is the consideration of coupling among diverse data products, which is essential but often overlooked in prior studies. We properly classify data’s utility into endogenous and relational categories to disentangle the coupling. Despite the inherent non-convex nature of the optimization problem, we methodically derive the closed-form optimal solutions by decomposing the problem into several subproblems. Interestingly, we reveal that, under our proposed framework, sellers’ revenue initially remains steady with the increase of product coupling level, but begins to rise once the level exceeds a certain threshold due to the substitute effect. Finally, experimental results show that our proposed framework can improve the seller’s profit by up to 46.32% compared to traditional data trading methods in the current data market.

关键词： Couplings Games Big Data Data models Global communication Optimization

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