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Semi-supervised learning with local and global consistency by geodesic distance and sparse representation 1

3rd Sino-Foreign-Interchange Workshop on intelligent Science and intelligent Data Engineering, IScIDE 2012

作者： Gui, Jie Zhao, Zhongqiu Hu, Rongxiang Jia, Wei Intelligent Computing Lab. Hefei Institute of Intelligent Machines Chinese Academy of Sciences Hefei Anhui 230031 China State Key Laboratory for Novel Software Technology Nanjing University China College of Computer Science and Information Engineering Hefei University of Technology China Institue of Energy Safety Chinese Academy of Sciences Hefei Anhui 230031 China

ISBN: (数字)9783642366697

ISBN: (纸本)9783642366680

In many practical data mining applications, such as web categorization, key gene selection, etc., generally, unlabeled training examples are readily available, but labeled ones are fairly expensive to obtain. Therefore, in recent years, semi-supervised learning algorithms such as graph-based methods have attracted much attention. However, most of these traditional methods adopted a Gaussian function to calculate the edge weights of the graph. In this paper, a novel weight for semi-supervised graph-based methods is proposed. The new method adds the label information from problem into the target function, and adopts the geodesic distance rather than Euclidean distance as the measure of the difference between two data points when conducting the calculation. In addition, we also add class prior knowledge from problem into semi-supervised learning algorithm. Here we address the problem of learning with local and global consistency (LGC). It was found that the effect of class prior knowledge was probably different between under high label rate and low label rate. Furthermore, we integrate sparse representation (SR) in LGC algorithm. Experiments on a UCI data set show that our proposed method outperforms the original algorithms. © Springer-Verlag 2013.

关键词： Learning algorithms

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ROBUST MULTI-PATCH TRACKING

ROBUST MULTI-PATCH TRACKING

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IEEE International Conference on Image Processing

作者： Shanxin Yuan Jun Miao Laiyun Qing Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781479923427

In this paper, we propose a robust and fast multi-patch visual tracking algorithm within the Bayesian inference framework. The target template is initialized by selecting the object in the first frame manually and dividing it into small patches. For one certain frame, target candidates are sampled with the state transition model. Each candidate is divided into patches in the same way as the target template. By comparing the candidate's patches with the corresponding template patches, we can get the candidate's likelihood. The tracking result is the candidate which Maximum a Posteriori estimation. After that, tracking is continued using the Bayesian state inference and template update. Our approach can handle appearance variation, occlusion, illumination change, scale variation, rotation and cluttered background. The tracker is fast and performs favorably against several state-of-the-art trackers on challenging sequences.

关键词： Visual tracking Bayesian inference multi-patch fast robust Bayesian inference visual tracking Fasting jigs(templates) tracking Maximum a posteriori estimation Robustness Patches State Change candidate species

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EMPLOYING PLSA MODEL AND MAX-BISECTION FOR REFINING IMAGE ANNOTATION

EMPLOYING PLSA MODEL AND MAX-BISECTION FOR REFINING IMAGE AN...

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IEEE International Conference on Image Processing

作者： Dongping Tian Wenbo Zhang Xiaofei Zhao Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781479923427

We present a new method for refining image annotation by fusing probabilistic latent semantic analysis (PLSA) with max-bisection (MB). We first construct a PLSA model with asymmetric modalities to estimate the posterior probabilities of each annotating keyword for an image, and then a label similarity graph is built by a weighted linear combination of label similarity and visual similarity. Followed by the rank-two relaxation heuristics over the constructed label graph is employed to further mine the correlation of the keywords so as to capture the refining annotation, which plays a critical role in semantic based image retrieval. The novelty of our method mainly lies in two aspects: exploiting PLSA to accomplish the initial semantic annotation task and implementing max-bisection based on the rank-two relaxation algorithm over the weighted label graph to refine the candidate annotations generated by the PLSA. We evaluate our method on the standard Corel dataset and the experimental results are competitive to several state-of-the-art approaches.

关键词： Refining image annotation PLSA EM max-bisection image retrieval image retrieval images ANNOTATIONS Refining labelled graph Line graph Linear Combination Purification KEYWORD

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Security games with surveillance cost and optimal timing of attack execution

Security games with surveillance cost and optimal timing of ...

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12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013

作者： An, Bo Brown, Matthew Vorobeychik, Yevgeniy Tambe, Milind Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Southern California Los Angeles CA 90089 United States Sandia National Laboratories Livermore CA 94550 United States

ISBN: (纸本)9781627487665

Stackelberg games have been used in several deployed applications to allocate limited resources for critical infrastructure protection. These resource allocation strategies are randomized to prevent a strategic attacker from using surveillance to learn and exploit patterns in the allocation. Past work has typically assumed that the attacker has perfect knowledge of the defender's randomized strategy or can learn the defender's strategy after conducting a fixed period of surveillance. In consideration of surveillance cost, these assumptions are clearly simplistic since attackers may act with partial knowledge of the defender's strategies and may dynamically decide whether to attack or conduct more surveillance. In this paper, we propose a natural model of limited surveillance in which the attacker dynamically determine a place to stop surveillance in consideration of his updated belief based on observed actions and surveillance cost. We show an upper bound on the maximum number of observations the attacker can make and show that the attacker's optimal stopping problem can be formulated as a finite state space MDP. We give mathematical programs to compute optimal attacker and defender strategies. We compare our approaches with the best known previous solutions and experimental results show that the defender can achieve significant improvement in expected utility by taking the attacker's optimal stopping decision into account, validating the motivation of our work. Copyright © 2013, International Foundation for Autonomous Agents and Multiagent Systems (***). All rights reserved.

关键词： Game theory

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Genome-wide identification of cancer-related polyadenylated and non-polyadenylated RNAs in human breast and lung cell lines

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Science China(Life Sciences) 2013年第5期56卷 503-512,1-4页

作者： ZHAO GuoGuang JIAO Fei LIAO Qi LUO HaiTao LI Hui SUN Liang BU DeChao YU KunTao ZHAO Yi CHEN RunSheng Bioinformatic Research Group Key Laboratory of Intelligent Information ProcessingAdvanced Computing Research LaboratoryInstitute of Computing TechnologyChinese Academy of Sciences University of Chinese Academy of Sciences Department of Biochemistry and Molecular Biology Binzhou Medical College Department of Preventive Medicine School of MedicineNingbo University College of Computer Science and Technology Jilin University Bioinformatics Laboratory and National Laboratory of Biomacromolecules Institute of BiophysicsChinese Academy of SciencesBeijing 100101China

Eukaryotic mRNAs consist of two forms of transcripts:poly(A)+ and poly(A),based on the presence or absence of poly(A) tails at the 3 ***(A)+ mRNAs are mainly protein coding mRNAs,whereas the functions of poly(A) mRNA are largely *** studies have shown that a significant proportion of gene transcripts are poly(A) or bimorphic(containing both poly(A)+ and poly(A) transcripts).We compared the expression levels of poly(A) and poly(A)+ RNA mRNAs in normal and cancer cell *** also investigated the potential functions of these RNA transcripts using an integrative workflow to explore poly(A)+ and poly(A) transcriptome sequences between a normal human mammary gland cell line(HMEC) and a breast cancer cell line(MCF-7),as well as between a normal human lung cell line(NHLF) and a lung cancer cell line(A549).The data showed that normal and cancer cell lines differentially express these two forms of *** ontology(GO) annotation analyses hinted at the functions of these two groups of transcripts and grouped the differentially expressed genes according to the form of their *** data showed that cell cycle-,apoptosis-,and cell death-related functions corresponded to most of the differentially expressed genes in these two forms of transcripts,which were also associated with the ***,translational elongation and translation functions were also found for the poly(A) protein-coding genes in cancer cell *** demonstrate that poly(A) transcripts play an important role in cancer development.

关键词： polyadenylation non-polyadenylation function annotation high throughput sequencing cancer bioinformatics

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Exploit spatial relationships among pixels for saliency region detection using topic model

Exploit spatial relationships among pixels for saliency regi...

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19th International Conference on Advances in Multimedia Modeling, MMM 2013

作者： Jiang, Guang Liu, Xi Yue, JinPeng Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100049 China Fujitsu Research and Development Center Co. LTD Beijing 100025 China

ISBN: (纸本)9783642357244

In this paper, we describe an approach to saliency detection as a two-category (salient or not) soft clustering using topic model. In order to simulate human's paralleled visual neural perception, many subregions are sampling from an image, where each one is considered as a set of colors from a codebook, which is a color palette for the image. We assume salient pixels would appear spatial adjacent more possibly, therefore in a same sub-region, while less salient pixels would either. Consequently, all the sub-regions are clustered into two assumed topics with probabilities: "salient"/ "non-salient", while "salient" one is decided to give saliency value of each pixel according to its posterior conditional probability. Our method will give a global saliency map with full resolution, and experiments illustrate it is competitive with the state-of-art methods. © Springer-Verlag 2013.

关键词： Pixels

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Forward non-rigid motion tracking for facial MoCap

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The Visual Computer 2013年第2期30卷 139-157页

作者： Xiaoyong Fang Xiaopeng Wei Qiang Zhang Dongsheng Zhou Key Laboratory of Advanced Design and Intelligent Computing (Dalian University) Ministry of Education Dalian China School of Computer and Information Science Hunan Institute of Technology Hengyang China

For the existing motion capture (MoCap) data processing methods, manual interventions are always inevitable, most of which are derived from the data tracking process. This paper addresses the problem of tracking non-rigid 3D facial motions from sequences of raw MoCap data in the presence of noise, outliers and long time missing. We present a novel dynamic spatiotemporal framework to automatically solve the problem. First, based on a 3D facial topological structure, a sophisticated non-rigid motion interpreter (SNRMI) is put forward; together with a dynamic searching scheme, it cannot only track the non-missing data to the maximum extent but recover missing data (it can accurately recover more than five adjacent markers under long time (about 5 seconds) missing) accurately. To rule out wrong tracks of the markers labeled in open structures (such as mouth, eyes), a semantic-based heuristic checking method was raised. Second, since the existing methods have not taken the noise propagation problem into account, a forward processing framework is presented to solve the problem. Another contribution is the proposed method could track facial non-rigid motions automatically and forward, and is believed to greatly reduce even eliminate the requirements of human interventions during the facial MoCap data processing. Experimental results proved the effectiveness, robustness and accuracy of our system.

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The Sound and Complete <i>R</i>-Calculi with Respect to Pseudo-Revision and Pre-Revision

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International Journal of Intelligence Science 2013年第2期3卷 110-117页

作者： Wei Li Yuefei Sui Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China State Key Laboratory of Software Development Environment Beijing University of Aeronautics and Astronautics Beijing China

The AGM postulates ([1]) are for the belief revision (revision by a single belief), and the DP postulates ([2]) are for the iterated revision (revision by a finite sequence of beliefs). Li [3] gave an R-calculus for R-configurations △|Γ, where Δ is a set of literals, and Γ is a finite set of formulas. We shall give two R-calculi such that for any consistent set Γ and finite consistent set △ of formulas in the propositional logic, in one calculus, there is a pseudo-revision Θ of Γ by Δ such that is provable and and in another calculus, there is a pre-revision Ξ of Γ by Δ such that is provable, and for some pseudo-revision Θ;and prove that the deduction systems for both the R-calculi are sound and complete with the pseudo-revision and the pre-revision, respectively.

关键词： Belief Revision R-Calculus Maximal Consistent Set Pseudo-Revision Pre-Revision

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A novel neural network classification model based on covering and Affinity Propagation clustering algorithm

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Journal of Computational information Systems 2013年第7期9卷 2565-2573页

作者： Li, Hui Ding, Shifei School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Jiangsu Normal University Xuzhou 221116 China

Affinity Propagation (AP) algorithm can automatically determine the cluster center and does not need a pre-determined number of clustering. This paper presents a novel neural network classification model, using AP clustering method as a pre-processor to cluster high dimensional massive data samples, and combining covering algorithm to automatically determine the center of the covering, and calculating its radius, and then converting these parameters into the weights and thresholds of the hidden layer of classification neural network. The number of hidden layer neurons is the number of covering. The output layer is the M-P neuron layer. By evaluating the input feature of hidden layer to complete the mapping from covering to the output, and gain the corresponding output category of the input feature. Simulation results show that our proposed neural network classification model can get better performance. Copyright © 2013 Binary information Press.

关键词： Clustering algorithms

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Compressed sensing based on best wavelet packet basis for image processing

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Journal of Computers (Finland) 2013年第8期8卷 1947-1950页

作者： Li, Zhe Tao Xie, Jing Xiong Yu, Zu Guo Tu, Deng Biao Choi, Young June The College of Information Engineering Xiangtan University Hunan 411105 China School of Computer National University of Defense Technology Hunan 410073 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Hunan 411105 China School of Mathematics and Computational Science Xiangtan University Hunan 411105 China National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing 100029 China Department of Information and Computer Engineering Ajou University Suwon 443749 Korea Republic of

In this paper, an algorithm named best wavelet packet tree decomposition (BWPTD) is proposed for image compression. In order to obtain better sparse representation of image, best wavelet packet basis is introduced to decompose image signal in the algorithm. Experimental results show that BWPTD is better than single layer wavelet decompression (SLWD) and original compressed sensing (OCS) in peak signal to noise ratio (PSNR) by 2db and 8db, respectively. In addition, the reconstruction time of BWPTD is only half as that of SLWD and OCS. © 2013 ACADEMY PUBLISHER.

关键词： Compressed sensing

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