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

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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Converting continuous-space language models into N-gram language models for statistical machine translation

Converting continuous-space language models into N-gram lang...

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2013 Conference on Empirical Methods in Natural Language processing, EMNLP 2013

作者： Wang, Rui Utiyama, Masao Goto, Isao Sumita, Eiichro Zhao, Hai Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong Unviersity Shanghai200240 China Multilingual Translation Laboratory MASTAR Project National Institute of Information and Communications Technology 3-5 Hikaridai Keihanna Science City Kyoto619-0289 Japan MOE-Microsoft Key Lab. for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong Unviersity Shanghai200240 China

ISBN: (纸本)9781937284978

Neural network language models, or continuous-space language models (CSLMs), have been shown to improve the performance of statistical machine translation (SMT) when they are used for reranking n-best translations. However, CSLMs have not been used in the first pass decoding of SMT, because using CSLMs in decoding takes a lot of time. In contrast, we propose a method for converting CSLMs into back-off n-gram language models (BNLMs) so that we can use converted CSLMs in decoding. We show that they outperform the original BNLMs and are comparable with the traditional use of CSLMs in reranking. © 2013 Association for Computational Linguistics.

关键词： Decoding

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One Sound and Complete <i>R</i>-Calculus with Pseudo-Subtheory Minimal Change Property

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Journal of Computer and Communications 2013年第5期1卷 20-25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 axiom system is for the belief revision (revision by a single belief), and the DP axiom system is for the iterated revision (revision by a finite sequence of beliefs). Li [1] gave an R-calculus for R-configurations Δ|Γ,?where?Δ?is a set of atomic formulas or the negations of atomic formulas, and?Γ?is a finite set of formulas. In propositional logic programs, one R-calculus N will be given in this paper, such that N is sound and complete with respect to operator s(Δ,t), where s(Δ,t)is a pseudo-theory minimal change of t by?Δ.

关键词： Belief Revision R-Calculus Soundness and Completeness of a Calculus Pseudo-Subtheory

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The Sound and Complete R-Calculi with Respect to the Set-Based and Inference-Based Minimal Change

The Sound and Complete R-Calculi with Respect to the Set-Bas...

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2013 Asia-Pacific Computational Intelligence and information technology Conference(APCIIT 2013)

作者： LI WEI YUEFEI SUI State Key Laboratory of Software Development Environment Beijing University of Aeronautics and Astronautics Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences

The AGM axiom system is for the belief revision(revision by a single belief), and the DP axiom system is for the iterated revision(revision by a finite sequence of beliefs). Li[1] gave an R-calculus for R-configurations |Γ, where is a set of atomic formulas or the negations of atomic formulas, and Γ is a finite set of formulas. The set-based minimal change and inference-based minimal change are distinguished in this paper, and two R- calculi V and N are given so that V and N are sound and complete with respect to the set-based minimal change and the inference-based minimal change, respectively.

关键词： Belief Revision,R-Calculus,Minimal Change,Contraction,Soundness and Completeness.

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One Sound and Complete R-Calculus with Pseudo-Subtheory Minimal Change Property

One Sound and Complete R-Calculus with Pseudo-Subtheory Mini...

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2013 Conference on Artificial Intelligence and Data Mining(AIDM 2013);2013 Business Economics and Investment Conference(BEI 2013);2013 Water Pollution and Treatment Conference(WPT 2013)

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

The AGM axiom system is for the belief revision (revision by a single belief),and the DP axiom system is for the iterated revision (revision by a finite sequence of beliefs).Li [1] gave an R-calculus for R-configurations Δ| Γ,where Δ is a set of atomic formulas or the negations of atomic formulas,and Γ is a finite set of *** propositional logic programs,one R-calculus N will be given in this paper,such that N is sound and complete with respect to operator s (Δ,t),where s (Δ,t)is a pseudo-theory minimal change of t by Δ .

关键词：

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SALIENT REGION DETECTION VIA TEXTURE-SUPPRESSED BACKGROUND CONTRAST

SALIENT REGION DETECTION VIA TEXTURE-SUPPRESSED BACKGROUND C...

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IEEE International Conference on Image processing

作者： Jiamei Shuai Laiyun Qing Jun Miao Zhiguo Ma Xilin Chen University of Chinese Academy of Sciences Beijing 100049 China Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing 100190 China

ISBN: (纸本)9781479923427

We propose a novel salient region detection algorithm by texture-suppressed background contrast. We employ a structure extraction algorithm to suppress the small scale textures which are supposed to be not sensitive for human vision system. Then the texture-suppressed image is segmented into homogeneous superpixels. Motivated by the observation that the spatial distribution of the background has a high probability on the boundaries of images, we estimate the background as superpixels near the image boundaries. The saliency of each superpixel is then defined as the summation of its k minimum color distances to the estimated background super-pixels. Finally a post-processing process involving spatial and color adjacency is employed to generate a per-pixel saliency map. Experimental results demonstrate that the proposed method outperforms the state-of-the-art approaches.

关键词： Salient region detection Background contrast Texture suppression Superpixels BACKGROUND images Summation computer vision Boundary value problems Grain boundaries boundary layer Color Detection algorithms

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INSTANCE-SPECIFIC CANONICAL CORRELATION ANALYSIS FOR POSE ALIGNMENT

INSTANCE-SPECIFIC CANONICAL CORRELATION ANALYSIS FOR POSE AL...

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IEEE International Conference on Image processing

作者： Deming Zhai Hong Chang Xilin Chen Wen Gao School of Computer Science and Technology Harbin Institute of Technology Harbin China 150001 Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences (CAS) Beijing China 100080

ISBN: (纸本)9781479923427

Canonical correlation analysis (CCA) based methods achieve great success for pose alignment. However, CCA has limitations as a linear and global algorithm. Although some variants have been proposed to overcome the limitations, neither of them achieves locality and nonlinearity at the same time. In this paper, we propose a novel algorithm called Instance-Specific Canonical Correlation Analysis (ISCCA), which approximates the nonlinear data by computing the instance specific projections along the smooth curve of the manifold. Based on the framework of least squares regression, CCA is extended to the instance-specific case which obtains a set of locally-linear smooth but globally-nonlinear transformations. The optimization problem is proved to be convex and could be solved efficiently by alternating optimization. And the globally optimal solutions could be achieved with theoretical guarantee. Experimental results for pose alignment demonstrate the effectiveness of our proposed method.

关键词： proposed alignment transofrmations Alignment Posing optimal solution multivariate analysis nonlinearity Manifolds Convexity

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pNovo+: De Novo Peptide Sequencing and Assembly Using Complementary HCD and ETD Tandem Mass Spectra

pNovo+: De Novo Peptide Sequencing and Assembly Using Comple...

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第八届中国蛋白质组学大会

作者： Hao Chi Haifeng Chen Kun He Long Wu Bing Yang Rui-Xiang Sun Jianyun Liu Wen-Feng Zeng Chun-Qing Song Si-Min He Meng-Qiu Dong Key Lab of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China National Institute of Biological SciencesBeijingBeijing 102206China Laboratory of Intelligent Recognition and Image ProcessingBeijing Key Laboratory of Digital MediaBeihang UniversityBeijing100191China

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Progressive Image Restoration through Hybrid Graph Laplacian Regularization

Progressive Image Restoration through Hybrid Graph Laplacian...

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Data Compression Conference (DCC)

作者： Deming Zhai Xianming Liu Debin Zhao Hong Chang Wen Gao School of Computer Science and Technology Harbin Institute of Technology Harbin China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Harbin Institute of Technology Harbin Heilongjiang CN

ISBN: (纸本)9781467360371

In this paper, we propose a unified framework to perform progressive image restoration based on hybrid graph Laplacian regularized regression. We first construct a multi-scale representation of the target image by Laplacian pyramid, then progressively recover the degraded image in the scale space from coarse to fine so that the sharp edges and texture can be eventually recovered. On one hand, within each scale, a graph Laplacian regularization model represented by implicit kernel is learned which simultaneously minimizes the least square error on the measured samples and preserves the geometrical structure of the image data space by exploring non-local self-similarity. In this procedure, the intrinsic manifold structure is considered by using both measured and unmeasured samples. On the other hand, between two scales, the proposed model is extended to the parametric manner through explicit kernel mapping to model the inter-scale correlation, in which the local structure regularity is learned and propagated from coarser to finer scales. Experimental results on benchmark test images demonstrate that the proposed method achieves better performance than state-of-the-art image restoration algorithms.

关键词： Kernel Noise Image restoration Laplace equations Noise measurement Manifolds Linear programming

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