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International Joint Conference on Neural Networks

作者： Xiang Zhang Naiyang Guan Long Lan Dacheng Tao Zhigang Luo Science and Technology on Parallel and Distributed Processing Laboratory School of Computer Science National University of Defense Technology Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology

ISBN: (纸本)9781479914821

Projective non-negative matrix factorization (PNMF) projects a set of examples onto a subspace spanned by a non-negative basis whose transpose is regarded as the projection matrix. Since PNMF learns a natural parts-based representation, it has been successfully used in text mining and pattern recognition. However, it is non-trivial to analyze the convergence of the optimization algorithms for PNMF because its objective function is non-convex. In this paper, we propose a Box-constrained PNMF (BPNMF) method to overcome this deficiency of PNMF. In particular, BPNMF introduces an auxiliary variable, i.e., the coefficients of examples, and incorporates the following two types of constraints: 1) each entry of the basis is non-negative and upper-bounded, i.e., box-constrained, and 2) the coefficients equal to the projected points of the examples. The first box constraint makes the basis to be bound and the second equality constraint keeps its equivalence to PNMF. Similar to PNMF, BPNMF is difficult because the objective function is non-convex. To solve BPNMF, we developed an efficient algorithm in the frame of augmented Lagrangian multiplier (ALM) method and proved that the ALM-based algorithm converges to local minima. Experimental results on two face image datasets demonstrate the effectiveness of BPNMF compared with the representative methods.

关键词： Accuracy Linear programming Training Convergence Optimization Face Educational institutions

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Soft-Constrained Nonnegative Matrix Factorization via Normalization

Soft-Constrained Nonnegative Matrix Factorization via Normal...

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International Joint Conference on Neural Networks

作者： Long Lan Naiyang Guan Xiang Zhang Dacheng Tao Zhigang Luo Science and Technology on Parallel and Distributed Processing Laboratory School of Computer Science National University of Defense Technology Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology

ISBN: (纸本)9781479914821

Semi-supervised clustering aims at boosting the clustering performance on unlabeled samples by using labels from a few labeled samples. Constrained NMF (CNMF) is one of the most significant semi-supervised clustering methods, and it factorizes the whole dataset by NMF and constrains those labeled samples from the same class to have identical encodings. In this paper, we propose a novel soft-constrained NMF (SCNMF) method by softening the hard constraint in CNMF. Particularly, SCNMF factorizes the whole dataset into two lower-dimensional factor matrices by using multiplicative update rule (MUR). To utilize the labels of labeled samples, SCNMF iteratively normalizes both factor matrices after updating them with MURs to make encodings of labeled samples close to their label vectors. It is therefore reasonable to believe that encodings of unlabeled samples are also close to their corresponding label vectors. Such strategy significantly boosts the clustering performance even when the labeled samples are rather limited, e.g., each class owns only a single labeled sample. Since the normalization procedure never increases the computational complexity of MUR, SCNMF is quite efficient and effective in practices. Experimental results on face image datasets illustrate both efficiency and effectiveness of SCNMF compared with both NMF and CNMF.

关键词： Matrix decomposition Encoding Vectors Clustering methods Clustering algorithms Time complexity Face

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Assessing the Impact of Cascading Failures on the Interdomain Routing System of the Internet

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New Generation Computing 2014年第3期32卷 237-255页

作者： Liu, Yujing Peng, Wei Su, Jinshu Wang, Zhilin College of Computer National University of Defense Technology Hunan Changsha China College of Computer Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Hunan Changsha China Education Department National University of Defense Technology Hunan Changsha China

The Internet is a typical complex network, whose traffic load is controlled by the inter-domain routing system. Due to the co-location of data plane and control plane of Border Gateway Protocol, the survivability of inter-domain routing system is sensitive to severe congestion. Therefore, an initial outage may lead to a cascade of failures in the Internet. But the cascading failures on links are able to be automatically restored when the congestion is mitigated. In this paper, we propose a model - CAFEIN for characterizing this special process. Based on CAFEIN, we assess the difference of impact under intentional attacks and random breakdowns; identify the worst affected part of the Internet; and study the propagation of cascading failures. Through simulations, we find that the cascading failures bring a great deal of added burden to the routing system. However, the cascading effect is amplified globally when the relative capacity of links is very low. Moreover, the difference of impact between intentional attack and random breakdown is not as prominent as previous research due to the unique automatic-restoration process.

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Power and performance analysis of the Graph 500 benchmark on the Single-chip Cloud computer

Power and performance analysis of the Graph 500 benchmark on...

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International Conference on Cloud Computing and Internet of Things (CCIOT)

作者： Zhiquan Lai King Tin Lam Cho-Li Wang Jinshu Su College of Computer National University of Defense Technology Changsha China Department of Computer Science The University of Hong Kong Hong Kong China National Key Laboratory of Parallel and Distributed Processing (PDL) Changsha China

ISBN: (纸本)9781479947638

The concerns of data-intensiveness and energy awareness are actively reshaping the design of high-performance computing (HPC) systems nowadays. The Graph500 is a widely adopted benchmark for evaluating the performance of computing systems for data-intensive workloads. In this paper, we introduce a data-parallel implementation of Graph500 on the Intel Single-chip Cloud computer (SCC). The SCC features a non-coherent many-core architecture and multi-domain on-chip DVFS support for dynamic power management. With our custom-made shared virtual memory programming library, memory sharing among threads is done efficiently via the shared physical memory (SPM) while the library has taken care of the coherence. We conduct an in-depth study on the power and performance characteristics of the Graph500 workloads running on this system with varying system scales and power states. Our experimental results are insightful for the design of energy-efficient many-core systems for data-intensive applications.

关键词： Kernel Benchmark testing computer architecture Programming Power measurement Computational modeling Runtime

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MCHITS: Monte carlo based method for hyperlink induced topic search on networks

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Journal of Networks 2013年第10期8卷 2376-2382页

作者： Jin, Zhaoyan Shi, Dianxi Wu, Quanyuan Fan, Hua National Key Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha 410073 China

Hyperlink Induced Topic Search (HITS) is the most authoritative and most widely used personalized ranking algorithm on networks. The HITS algorithm ranks nodes on networks according to power iteration, and has high complexity of computation. This paper models the HITS algorithm with the Monte Carlo method, and proposes Monte Carlo based algorithms for the HITS computation. Theoretical analysis and experiments show that the Monte Carlo based approximate computing of the HITS ranking reduces computing resources a lot while keeping higher accuracy, and is significantly better than related works. © 2013 ACADEMY PUBLISHER.

关键词： Monte Carlo methods

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Translation Non-negative Matrix Factorization with Fast Optimization

Translation Non-negative Matrix Factorization with Fast Opti...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Yuanyuan Wang Naiyang Guan Bin Mao Xuhui Huang Zhigang Luo Department of Basic Courses Army Officer Academy Science and Technology on Parallel and Distributed Processing Laboratory College of Computer Science National University of Defense Technology College of Science National University of Defense Technology College of Computer Science National University of Defense Technology

ISBN: (纸本)9781479938414

Non-negative matrix factorization (NMF) reconstructs the original samples in a lower dimensional space and has been widely used in pattern recognition and data mining because it usually yields sparse representation. Since NMF leads to unsatisfactory reconstruction for the datasets that contain translations of large magnitude, it is required to develop translation NMF (TNMF) to first remove the translation and then conduct a decomposition. However, existing multiplicative update rule based algorithm for TNMF is not efficient enough. In this paper, we reformulate TNMF and show that it can be efficiently solved by using the state-of-the-art solvers such as NeNMF. Experimental results on face image datasets confirm both efficiency and effectiveness of the reformulated TNMF.

关键词： Non-negative matrix factorization (NMF) Translation transformation NeNMF

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RAFlow: Read Ahead Accelerated I/O Flow through Multiple Virtual Layers

RAFlow: Read Ahead Accelerated I/O Flow through Multiple Vir...

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International Conference on Networking, Architecture, and Storage (NAS)

作者： Zhaoning Zhang Kui Wu Huiba Li Jinghua Feng Yuxing Peng Xicheng Lu National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology China Computer Science Department University of Victoria B.C. Canada National Super Computing Center Tianjin China

Virtualization is the foundation for cloud computing, and the virtualization can not be achieved without software defined, elastic, flexible and scalable virtual layers. Unfortunately, if multiple virtual storage devices are chained together, the system may be subject to severe performance degradation. While the read-ahead (RA) mechanism in storage devices plays a very important role to improve I/O performance, RA may not be effective as expected for multiple virtualization layers, since it is originally designed for one layer only. When I/O requests are passed through a long I/O path, they may trigger a chain reaction and lead to unnecessary data transmission and thus bandwidth waste. In this paper, we study the dynamic behavior of RA through multiple I/O layers and demonstrate that if controlled well, RA can greatly accelerate I/O speed. We present RAFlow, a RA control mechanism, to effectively improve I/O performance by strategically expanding RA window at each layer. Our real-world experiments show that it can achieve 20% to 50% performance improvement in I/O paths with up to 8 virtualized storage devices.

关键词： Radio access networks Acceleration distributed databases Performance evaluation Synchronization Benchmark testing Degradation

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Single image defogging with single and multiple hybrid scattering model

Single image defogging with single and multiple hybrid scatt...

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International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)

作者： Weijiang Feng Naiyang Guan Xiang Zhang Xuhui Huang Zhigang Luo Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha Hunan P.R. China Department of Computer Science and Technology College of Computer National University of Defense Technology Changsha Hunan P.R. China

Image defogging (IDF) removes influences of fogs from an image to improve its quality. Since defogged images can significantly boost the performance of subsequent processing, IDF has attracted many attentions from the computer vision community. However, existing IDF algorithms are built on the assumption that light is scattered once by a grain. Since such assumption is violated if images are contaminated by dense haze or heavy fog, traditional IDF algorithms often fail in this situation. In this paper, we propose a hybrid image defogging (HIDF) algorithm to overcome this deficiency. In particular, HIDF applies the single scattering physics model (SSPM) to pixels dominated by single scattering of light, and applies the multiple scattering physics model (MSPM) to remaining pixels. To distinguish two types of pixels, HIDF utilizes the optical thickness of corresponding pixels. If optical thickness is smaller than a threshold that determines whether the single scattering or the multiple scattering dominates, HIDF applies the SSPM, and HIDF applies the MSPM otherwise. Experimental results on several popular foggy images demonstrate that HIDF competes with the state-of-the-art algorithms, and show the promise of HIDF for defogging heavily foggy images.

关键词： Meteorology Optical imaging Optical scattering Atmospheric modeling Image color analysis

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A Runtime Verification Based Trace-Oriented Monitoring Framework for Cloud Systems

A Runtime Verification Based Trace-Oriented Monitoring Frame...

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IEEE International Conference on Software Reliability Engineering Workshops (ISSRE Wksp)

作者： Jingwen Zhou Zhenbang Chen Ji Wang Zibin Zheng Wei Dong College of Computer National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen China

Cloud computing provides a new paradigm for resource utilization and sharing. However, the reliability problems, like system failures, often happen in cloud systems and bring enormous loss. Trace-oriented monitoring is an important runtime method to improve the reliability of cloud systems. In this paper, we propose to bring runtime verification into trace-oriented monitoring, to facilitate the specification of monitoring requirements and to improve the efficiency of monitoring cloud systems. Based on a data set collected from a cloud storage system in a real environment, we validate our approach by monitoring the critical properties of the storage system. The preliminary experimental results indicate the promise of our approach.

关键词： Monitoring Runtime Cloud computing Educational institutions Reliability Google computers

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distributed Relation Discovery in Internet of Things

Distributed Relation Discovery in Internet of Things

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International Conference on Cloud Computing and Big Data (CCBD)

作者： Weiping Zhu Hongliang Lu Xiaohui Cui International School of Software Wuhan University China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology China Department of Computing Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)9781479966226

Internet of things is an emerging technology that aims to connect various smart objects in our daily life. It facilitates the information exchange and control among objects. In the Internet of things, it is important to discover various relations among objects for analyzing and mining useful knowledge. Existing works on relation discovery mainly focus on centralized processing. It is not suitable for Internet of things due to unavailable of server, one-point failure, computation bottleneck, and security and business concerns. In this paper, we propose a distributed approach to discover the relations among objects in Internet of things. We first build the distritbuted system model which may include multiple relation discovery tasks. Based on that, we design an approach utilizing distributed spanning tree to extract the relations. Rather than sending all the information to the server, the objects only need to send the information to a local leader object in our algorithm. We also discuss more about how to improve the performance of the proposed approach and how to relax the system constraints. Extensive simulation have been done and the results show that the proposed approach outperforms existing approaches in terms of the data amount of transmission.

关键词： Internet of things Synchronization Buildings Servers Algorithm design and analysis Delays

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