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Robust low-rank tensor factorization by cyclic weighted median

Science China(information Sciences) 2015年第5期58卷 145-155页

作者： MENG DeYu ZHANG Biao XU ZongBen ZHANG Lei GAO ChenQiang Institute for Information and System Sciences and Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Department of Computing Hong Kong Polytechnic University Chongqing Key Laboratory of Signal and Information Processing Chongqing University of Posts and Telecommunications

Low-rank tensor factorization(LRTF) provides a useful mathematical tool to reveal and analyze multi-factor structures underlying data in a wide range of practical applications. One challenging issue in LRTF is how to recover a low-rank higher-order representation of the given high dimensional data in the presence of outliers and missing entries, i.e., the so-called robust LRTF problem. The L1-norm LRTF is a popular strategy for robust LRTF due to its intrinsic robustness to heavy-tailed noises and outliers. However, few L1-norm LRTF algorithms have been developed due to its non-convexity and non-smoothness, as well as the high order structure of data. In this paper we propose a novel cyclic weighted median(CWM) method to solve the L1-norm LRTF problem. The main idea is to recursively optimize each coordinate involved in the L1-norm LRTF problem with all the others fixed. Each of these single-scalar-parameter sub-problems is convex and can be easily solved by weighted median filter, and thus an effective algorithm can be readily constructed to tackle the original complex problem. Our extensive experiments on synthetic data and real face data demonstrate that the proposed method performs more robust than previous methods in the presence of outliers and/or missing entries.

关键词： tensor factorization low-rank weighted median filter tensorface

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Video saliency prediction with optimized optical flow and gravity center bias

Video saliency prediction with optimized optical flow and gr...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Zhe Wu Li Su Qingming Huang Bo Wu Jian Li Guorong Li Key Lab on Big Data Mining and Knowledge Management University of Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing Institute of Computing Technology Beijing China Capital Medical University Beijing China Beijing University of Posts and Telecommunications China Beijing

ISBN: (纸本)9781467372596

Dynamic videos are viewed fundamentally different from static images. Besides spatial features, motion feature also plays an important role as a temporal factor. Most existing video saliency models usually employ optical flow to represent the motion feature. However, optical flow often suffers from the discontinuity problem. And we also notice that human fixations in one single video frame are much sparser than that in an identical still picture. However, many spatial saliency models take each video frame as static image independently. In this paper, we predict the dynamic visual saliency by fusing spatial and temporal features. In order to construct the temporal relationships among a set of successive frames, we introduce a smoothness operator in optical flow field to obtain more accurate motion feature. Then, considering the sparse property of video saliency, we adapt the weights of the regions surrounding to the saliency gravity center in the final maps. The experiments show that our model is more consistent with humans eye-tracking benchmarks than the state-of-the-art models.

关键词： Optical imaging Gravity Computational modeling Visualization Biomedical optical imaging Adaptation models Feature extraction

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Deterministic realization of collective measurements via photonic quantum walks

arXiv

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arXiv 2017年

作者： Hou, Zhibo Tang, Jun-Feng Shang, Jiangwei Zhu, Huangjun Li, Jian Yuan, Yuan Wu, Kang-Da Xiang, Guo-Yong Li, Chuan-Feng Guo, Guang-Can Key Laboratory of Quantum Information University of Science and Technology of China CAS Hefei230026 China Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China Hefei230026 China Naturwissenschaftlich-Technische Fakultät Universität Siegen Siegen57068 Germany Beijing Key Laboratory of Nanophotonics Ultrafine Optoelectronic Systems School of Physics Beijing Institute of Technology Beijing100081 China Institute for Theoretical Physics University of Cologne Cologne50937 Germany Department of Physics Center for Field Theory and Particle Physics Fudan University Shanghai200433 China Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China State Key Laboratory of Surface Physics Fudan University Shanghai200433 China Collaborative Innovation Center of Advanced Microstructures Nanjing210093 China Institute of Signal Processing Transmission Nanjing University of Posts and Telecommunications Nanjing210003 China Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Nanjing210003 China

Collective measurements on identically prepared quantum systems can extract more information than local measurements, thereby enhancing information-processing efficiency. Although this nonclassical phenomenon has been known for two decades, it has remained a challenging task to demonstrate the advantage of collective measurements in experiments. Here we introduce a general recipe for performing deterministic collective measurements on two identically prepared qubits based on quantum walks. Using photonic quantum walks, we realize experimentally an optimized collective measurement with fidelity 0.9946 without post selection. As an application, we achieve the highest tomographic efficiency in qubit state tomography to date. Our work offers an effective recipe for beating the precision limit of local measurements in quantum state tomography and metrology. In addition, our study opens an avenue for harvesting the power of collective measurements in quantum information processing and for exploring the intriguing physics behind this power. Copyright © 2017, The Authors. All rights reserved.

关键词： Quantum optics

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Memory bandwidth optimization of SpMV on GPGPUs

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Frontiers of Computer Science 2015年第3期9卷 431-441页

作者： Chenggang Clarence YAN Hui YU Weizhi XU Yingping ZHANG Bochuan CHEN Zhu TIAN Yuxuan WANG Jian YIN Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Institute of Microelectronics Tsinghua University Beijing 100084 China Automation Department Tsinghua University Beijing 100084 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China State Grid Information & Communication Company of Hunan EPC Changsha 410007 China Department of Computer Shandong University Weihai 250101 China

It is an important task to improve performance for sparse matrix vector multiplication （SpMV）, and it is a difficult task because of its irregular memory access. Gen- eral purpose GPU （GPGPU） provides high computing abil- ity and substantial bandwidth that cannot be fully exploited by SpMV due to its irregularity. In this paper, we propose two novel methods to optimize the memory bandwidth for SpMV on GPGPU. First, a new storage format is proposed to exploit memory bandwidth of GPU architecture more effi- ciently. The new storage format can ensure that there are as many non-zeros as possible in the format which is suitable to exploit the memory bandwidth of the GPU. Second, we pro- pose a cache blocking method to improve the performance of SpMV on GPU architecture. The sparse matrix is partitioned into sub-blocks that are stored in CSR format. With the block- ing method, the corresponding part of vector x can be reused in the GPU cache, so the time to access the global memory for vector x is reduced heavily. Experiments are carried out on three GPU platforms, GeForce 9800 GX2, GeForce GTX 480, and Tesla K40. Experimental results show that both new methods can efficiently improve the utilization of GPU mem- ory bandwidth and the performance of the GPU.

关键词： GPGPU performance tuning SpMV cacheblocking memory bandwidth

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Novel Detection Service Method for Moving Object in IOT

Novel Detection Service Method for Moving Object in IOT

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2016 3rd International Conference on Materials Engineering,Manufacturing technology and Control(ICMEMTC 2016)

作者： Jie Chen Degan Zhang School of Electronic and Information Engineering Tianjin Vocational Institute Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education

In embedded Internet of Things(IOT) environment, there are the troubles such as complex background, illumination changes, shadows and other factors for detecting moving object, so we put forward a new detection service method through mixing Gaussian Mixture Model(GMM), edge detection service method and continuous frame difference method in this paper. In time domain, the new method uses GMM to model and updates the background. In spatial domain, it uses the hybrid detection service method which mixes edge detection service method, continuous frame difference method and GMM to get initial contour of moving object, and gets ultimate moving object. This method not only can well adapt to the illumination gradients and background disturbance occurred on scene, but also can well solve some problems such as inaccurate target detection, incomplete edge detection, cavitation and ghost which usually appears in traditional method. As experimental result showing, this method holds better real-time and robustness. It is not only easily implemented, but also can accurately detect moving object.

关键词： GMM embedded IOT moving object detection service

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Abstractive multi-document summarization with semantic information extraction

Abstractive multi-document summarization with semantic infor...

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Conference on Empirical Methods in Natural Language processing, EMNLP 2015

作者： Li, Wei Key Lab of Intelligent Info. Processing Institute of Computing Technology CAS Beijing100190 China

ISBN: (纸本)9781941643327

This paper proposes a novel approach to generate abstractive summary for multiple documents by extracting semantic information from texts. The concept of Basic Semantic Unit (BSU) is defined to describe the semantics of an event or action. A semantic link network on BSUs is constructed to capture the semantic information of texts. Summary structure is planned with sentences generated based on the semantic link network. Experiments demonstrate that the approach is effective in generating informative, coherent and compact summary. © 2015 Association for Computational Linguistics.

关键词： Semantics

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Bayesian localization microscopy based on intensity distribution of fluorophores

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Protein & Cell 2015年第3期6卷 211-220页

作者： Fan Xu Mingshu Zhang Zhiyong Liu Pingyong Xu Fa Zhang Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Laboratory of Non Coding RNA Institute of Biophysics Chinese Academy of Sciences Beijing 100101 China

Super-resolution microscopy techniques have overcome the limit of optical diffraction. Recently, the Bayesian analysis of Bleaching and Blinking data （3B） method has emerged as an important tool to obtain super-resolution fluorescence images. 3B uses the change in information caused by adding or removing fiuorophores in the cell to fit the date. When adding a new fluorophore, 3B selects a random initial position, optimizes this position and then determines its reliability. However, the fluorophores are not evenly distributed in the entire image region, and the fluorescence intensilty at a given position positively correlates with the probability of observing a fluorophore at this position. In this paper, we present a Bayesian analysis of Bleaching and Blinking microscopy method based on fluorescence intensity distribution （FID3B）. We utilize the intensity distribution to select more reliable positions as the initial positions of fluorophores. This approach can improve the reconstruction results and significantly reduce the computational time. We validate the perfor. mance of our method using both simulated date and experimental date from cellular structures. The results confirm the effectiveness of our method.

关键词： super-resolution fluorescence image 3B,intensity distribution

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An improved reference point sampling method on Pareto optimal front

An improved reference point sampling method on Pareto optima...

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Congress on Evolutionary Computation

作者： Cheng He Linqiang Pan Hang Xu Ye Tian Xingyi Zhang Laboratory of Image Information Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei China Huazhong University of Science and Technology Wuhan Hubei CN Department of Computer Science Xiamen University Xiamen Fujian China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei Anhui China

ISBN: (纸本)9781509006243

In this paper, we propose a sampling approach of reference points used for performance metrics of multi-objective evolutionary algorithms. Traditional reference point sampling methods, such as the Das and Dennis method, usually sample the reference points via a set of uniformly distributed weight vectors generated on an ideal hyper-plane in objective space, which however often ignore the geometric shape of a specific Pareto front. Therefore, we propose a novel reference point sampling approach by taking the specific shape of the Pareto optimal front to be tackled into account for measuring the performance of multi-objective evolutionary algorithms. The performance of the proposed reference point sampling method against the other two state-of-the-art sampling methods is tested on six test instances in various conditions, which clearly demonstrate the effectiveness and superiority of the proposed sampling method.

关键词： Sampling methods Shape Convergence Evolutionary computation Optimization Euclidean distance

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Casict-dcu participation in wmt2015 metrics task 10

Casict-dcu participation in wmt2015 metrics task

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10th Workshop on Statistical Machine Translation, WMT 2015 at the 2015 Conference on Empirical Methods in Natural Language processing, EMNLP 2015

作者： Yu, Hui Ma, Qingsong Wu, Xiaofeng Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Adapt Centre School of Computing Dublin City University

ISBN: (纸本)9781941643327

Human-designed sub-structures are required by most of the syntax-based machine translation evaluation metrics. In this paper, we propose a novel evaluation metric based on dependency parsing model, which does not need this human involvement. Experimental results show that the new single metric gets better correlation than METEOR on system level and is comparable with it on sentence level. To introduce more information, we combine the new metric with many other metrics. The combined metric obtains state-of-theart performance on both system level evaluation and sentence level evaluation on WMT 2014. © EMNLP 2015. All rights reserved.

关键词： Syntactics

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Exploiting structural similarity of log files in fault diagnosis for Web service composition

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CAAI Transactions on Intelligence technology 2016年第1期1卷 61-71页

作者： Xu Han Binyang Li Kam-Fai Wong Zhongzhi Shi Beijing Key Laboratory of Electronic System Reliability Technology Capital Normal University Beijing China University of International Relations Beijing China Department of Systems Engineering & Engineering Management The Chinese University of Hong Kong Hong Kong China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

With increasing deployment of Web services, the research on the dependability and availab.lity of Web service composition becomes more and more active. Since unexpected faults of Web service composition may occur in different levels at runtime, log analysis as a typical data- driven approach for fault diagnosis is more applicable and scalab.e in various architectures. Considering the trend that more and more service logs are represented using XML or JSON format which has good flexibility and interoperability, fault classification problem of semi-structured logs is considered as a challenging issue in this area. However, most existing approaches focus on the log content analysis but ignore the structural information and lead to poor performance. To improve the accuracy of fault classification, we exploit structural similarity of log files and propose a similarity based Bayesian learning approach for semi-structured logs in this paper. Our solution estimates degrees of similarity among structural elements from heterogeneous log data, constructs combined Bayesian network （CBN）, uses similarity based learning algorithm to compute probabilities in CBN, and classifies test log data into most probable fault categories based on the generated CBN. Experimental results show that our approach outperforms other learning approaches on structural log datasets.

关键词： Web services composition Fault diagnosis Combined Bayesian network （CBN） Similarity Probability

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